Information

15.6: Varying Rates of Speciation - Biology

15.6: Varying Rates of Speciation - Biology



We are searching data for your request:

Forums and discussions:
Manuals and reference books:
Data from registers:
Wait the end of the search in all databases.
Upon completion, a link will appear to access the found materials.

Two patterns are currently observed in the rates of speciation: gradual speciation and punctuated equilibrium.

Learning Objectives

  • Explain how the interaction of an organism’s population size in association with environmental changes can lead to different rates of speciation

Key Points

  • In the gradual speciation model, species diverge slowly over time in small steps while in the punctuated equilibrium model, a new species diverges rapidly from the parent species.
  • The two key influencing factors on the change in speciation rate are the environmental conditions and the population size.
  • Gradual speciation is most likely to occur in large populations that live in a stable environment, while the punctuation equilibrium model is more likely to occur in a small population with rapid environmental change.

Key Terms

  • punctuated equilibrium: a theory of evolution holding that evolutionary change tends to be characterized by long periods of stability, with infrequent episodes of very fast development
  • gradualism: in evolutionary biology, belief that evolution proceeds at a steady pace, without the sudden development of new species or biological features from one generation to the next

Varying Rates of Speciation

Scientists around the world study speciation, documenting observations both of living organisms and those found in the fossil record. As their ideas take shape and as research reveals new details about how life evolves, they develop models to help explain rates of speciation. In terms of how quickly speciation occurs, two patterns are currently observed: the gradual speciation model and the punctuated equilibrium model.

In the gradual speciation model, species diverge gradually over time in small steps. In the punctuated equilibrium model, a new species changes quickly from the parent species and then remains largely unchanged for long periods of time afterward. This early change model is called punctuated equilibrium, because it begins with a punctuated or periodic change and then remains in balance afterward. While punctuated equilibrium suggests a faster tempo, it does not necessarily exclude gradualism.

The primary influencing factor on changes in speciation rate is environmental conditions. Under some conditions, selection occurs quickly or radically. Consider a species of snails that had been living with the same basic form for many thousands of years. Layers of their fossils would appear similar for a long time. When a change in the environment takes place, such as a drop in the water level, a small number of organisms are separated from the rest in a brief period of time, essentially forming one large and one tiny population. The tiny population faces new environmental conditions. Because its gene pool quickly became so small, any variation that surfaces and that aids in surviving the new conditions becomes the predominant form.


Faster Speciation and Reduced Extinction in the Tropics Contribute to the Mammalian Latitudinal Diversity Gradient

Affiliations CNRS, UMR 7641 Centre de Mathématiques Appliquées (Ecole Polytechnique), Palaiseau, France, UMR 7204 MNHN–CNRS–UPMC Centre d'Ecologie et de Sciences de la Conservation, Museum National d'Histoire Naturelle, CP51, Paris, France

Affiliation CNRS, UMR 7641 Centre de Mathématiques Appliquées (Ecole Polytechnique), Palaiseau, France

Affiliation UMR 7204 MNHN–CNRS–UPMC Centre d'Ecologie et de Sciences de la Conservation, Museum National d'Histoire Naturelle, CP51, Paris, France

Affiliation CNRS, UMR 7641 Centre de Mathématiques Appliquées (Ecole Polytechnique), Palaiseau, France


Footnotes

Electronic supplementary material is available online at https://doi.org/10.6084/m9.figshare.c.5007827.

References

. 1971 Lepidoptera genetics . Oxford, UK : Pergamon Press Inc . Crossref, Google Scholar

. 2015 The blue butterfly Polyommatus (Plebicula) atlanticus (Lepidoptera, Lycaenidae) holds the record of the highest number of chromosomes in the non-polyploid eukaryotic organisms . Comp. Cytogenet. 9, 683-690. (doi:10.3897/CompCytogen.v9i4.5760) Crossref, PubMed, ISI, Google Scholar

Lukhtanov VA, Kandul NP, Plotkin JB, Dantchenko AV, Haig D, Pierce NE

. 2005 Reinforcement of pre-zygotic isolation and karyotype evolution in Agrodiaetus butterflies . Nature 436, 385-389. (doi:10.1038/nature03704) Crossref, PubMed, ISI, Google Scholar

Talavera G, Lukhtanov VA, Rieppel L, Pierce NE, Vila R

. 2013 In the shadow of phylogenetic uncertainty: the recent diversification of Lysandra butterflies through chromosomal change . Mol. Phylogenet. Evol. 69, 469-478. (doi:10.1016/j.ympev.2013.08.004) Crossref, PubMed, ISI, Google Scholar

. 2018 Evolutionary mechanisms of varying chromosome numbers in the radiation of Erebia butterflies . Genes 9, 1-9. (doi:10.3390/genes9030166) Crossref, ISI, Google Scholar

Guerrero RF, Kirkpatrick M

. 2014 Local adaptation and the evolution of chromosome fusions . Evolution 68, 2747-2756. (doi:10.1111/evo.12481) Crossref, PubMed, ISI, Google Scholar

. 2010 Chromosomal speciation revisited: rearranging theory with pieces of evidence . Trends Ecol. Evol. 25, 660-669. (doi:10.1016/j.tree.2010.07.008) Crossref, PubMed, ISI, Google Scholar

. 1958 Some peculiarities of spatially and sexually restricted gene exchange in the Erebia tyndarus group . Cold Spring Harb. Symp. Quant. Biol. 23, 319-325. (doi:10.1101/SQB.1958.023.01.032) Crossref, PubMed, Google Scholar

. 2009 Bad species . In Ecology of butterflies in Europe . Cambridge, UK : Cambridge University Press . Google Scholar

Lukhtanov VA, Dinca V, Friberg M, Šíchová J, Olofsson M, Vila R, Marec F, Wiklund C

. 2018 Versatility of multivalent orientation, inverted meiosis, and rescued fitness in holocentric chromosomal hybrids . Proc. Natl Acad. Sci. USA 115, E9610-E9619. (doi:10.1073/pnas.1802610115) Crossref, PubMed, ISI, Google Scholar

Hora KH, Marec F, Roessingh P, Menken SBJ

. 2019 Limited intrinsic postzygotic reproductive isolation despite chromosomal rearrangements between closely related sympatric species of small ermine moths (Lepidoptera: Yponomeutidae) . Biol. J. Linn. Soc. 128, 44-58. (doi:10.1093/biolinnean/blz090) Crossref, ISI, Google Scholar

Vershinina AO, Lukhtanov VA

. 2017 Evolutionary mechanisms of runaway chromosome number change in Agrodiaetus butterflies . Sci. Rep. 7, 8199. (doi:10.1038/s41598-017-08525-6) Crossref, PubMed, ISI, Google Scholar

Melters DP, Paliulis LV, Korf IF, Chan SWL

. 2012 Holocentric chromosomes: convergent evolution, meiotic adaptations, and genomic analysis . Chrom. Res. 20, 579-593. (doi:10.1007/s10577-012-9292-1) Crossref, PubMed, ISI, Google Scholar

Escudero M, Hahn M, Brown BH, Lueders K, Hipp AL

. 2016 Chromosomal rearrangements in holocentric organisms lead to reproductive isolation by hybrid dysfunction: the correlation between karyotype rearrangements and germination rates in sedges . Am. J. Bot. 103, 1529-1536. (doi:10.3732/ajb.1600051) Crossref, PubMed, ISI, Google Scholar

. 2017 Beyond speciation genes: an overview of genome stability in evolution and speciation . Curr. Op. Genet. Dev. 47, 17-23. (doi:10.1016/j.gde.2017.07.014) Crossref, PubMed, ISI, Google Scholar

. 2019 A butterfly chromonome reveals selection dynamics during extensive and cryptic chromosomal reshuffling . Sci. Adv. 5, eaau3648. (doi:10.1126/sciadv.aau3648) Crossref, PubMed, ISI, Google Scholar

Li S-F, Su T, Cheng G-Q, Wang B-X, Li X, Deng C-L, Gao W-J

. 2017 Chromosome evolution in connection with repetitive sequences and epigenetics in plants . Genes 8, 290. Crossref, ISI, Google Scholar

. 2014 The Glanville fritillary genome retains an ancient karyotype and reveals selective chromosomal fusions in Lepidoptera . Nat. Commun. 5, 4737. (doi:10.1038/ncomms5737) Crossref, PubMed, ISI, Google Scholar

. 2016 Multifaceted biological insights from a draft genome sequence of the tobacco hornworm moth, Manduca sexta . Insect Biochem. Mol. Biol. 76, 118-147. (doi:10.1016/j.ibmb.2016.07.005) Crossref, PubMed, ISI, Google Scholar

. 2016 The gene cortex controls mimicry and crypsis in butterflies and moths . Nature 534, 106-110. (doi:10.1038/nature17961) Crossref, PubMed, ISI, Google Scholar

2010 Extensive synteny conservation of holocentric chromosomes in Lepidoptera despite high rates of local genome rearrangements . Proc. Natl Acad. Sci. USA 107, 7680-7685. (doi:10.1073/pnas.0910413107) Crossref, PubMed, ISI, Google Scholar

. 1978 Modes of speciation . San Francisco, CA : W. H. Freeman . Google Scholar

. 1995 Species evolution . Cambridge, UK : Cambridge University Press . Google Scholar

. 2004 Speciation . Sunderland, MA : Sinauer Associates . Google Scholar

. 2003 Accumulating postzygotic isolation genes in parapatry: a new twist on chromosomal speciation . Evolution 57, 447-459. (doi:10.1111/j.0014-3820.2003.tb01537.x) Crossref, PubMed, ISI, Google Scholar

Garagna S, Page J, Fernandez-Donoso R, Zuccotti M, Searle JB

. 2014 The Robertsonian phenomenon in the house mouse: mutation, meiosis and speciation . Chromosoma 123, 529-544. (doi:10.1007/s00412-014-0477-6) Crossref, PubMed, ISI, Google Scholar

Potter S, Bragg JG, Blom MP. K., Deakin JE, Kirkpatrick M, Eldridge MD. B, Moritz C

. 2017 Chromosomal speciation in the genomics era: disentangling phylogenetic evolution of rock-wallabies . Front. Genet. 8, 10. (doi:10.3389/fgene.2017.00010) Crossref, PubMed, ISI, Google Scholar

. 2001 Chromosomal rearrangements and speciation . Trends Ecol. Evol. 16, 351-358. (doi:10.1016/S0169-5347(01)02187-5) Crossref, PubMed, ISI, Google Scholar

. 1994 Recombination suppressors and the evolution of new species . Heredity 73, 339-345. (doi:10.1038/hdy.1994.180) Crossref, PubMed, ISI, Google Scholar

Lanfear R, Kokko H, Eyre-Walker A

. 2014 Population size and the rate of evolution . Trends Ecol. Evol. 29, 33-41. (doi:10.1016/j.tree.2013.09.009) Crossref, PubMed, ISI, Google Scholar

Martinez PA, Jacobina UP, Fernandes RV, Brito C, Penone C, Amado TF, Fonseca CR, Bidau CJ

. 2017 A comparative study on karyotypic diversification rate in mammals . Heredity , 118, 366-373. (doi:10.1038/hdy.2016.110) Crossref, PubMed, ISI, Google Scholar

. 2002 Patterns of postzygotic isolation in Lepidoptera . Evolution 56, 1168-1183. (doi:10.1111/j.0014-3820.2002.tb01430.x) Crossref, PubMed, ISI, Google Scholar

. 2019 Macrosynteny analysis shows the absence of ancient whole-genome duplication in lepidopteran insects . Proc. Natl Acad. Sci. USA 116, 1816-1818. (doi:10.1073/pnas.1817937116) Crossref, PubMed, ISI, Google Scholar

Talla V, Suh A, Kalsoom F, Dinca V, Vila R, Friberg M, Wiklund C, Backström N

. 2017 Rapid increase in genome size as a consequence of transposable element hyperactivity in wood-white (Leptidea) butterflies . Genome Biol. Evol. 9, 2491-2505. (doi:10.1093/gbe/evx163) Crossref, PubMed, ISI, Google Scholar

Nguyen P, Carabajal Paladino L

. 2016 On the neo-sex chromosomes of Lepidoptera . In Evolutionary biology , 171-185. Cham, Switzerland : Springer International Publishing . Crossref, Google Scholar

Sahara K, Yoshido A, Traut W

. 2012 Sex chromosome evolution in moths and butterflies . Chromosome Res. 20, 83-94. (doi:10.1007/s10577-011-9262-z) Crossref, PubMed, ISI, Google Scholar

Fraïsse C, Picard MAL, Vicoso B

. 2017 The deep conservation of the Lepidoptera Z chromosome suggests a non-canonical origin of the W . Nat. Commun. 8, 1486. Crossref, PubMed, ISI, Google Scholar

Carabajal PLZ, Provazníková I., Berger M, Bass C, Aratchige NS, López SN, Marec F, Nguyen P

. 2019 Sex chromosome turnover in moths of the diverse superfamily Gelechioidea . Genome Biol. Evol. 11, 1307-1319. (doi:10.1093/gbe/evz075) Crossref, PubMed, ISI, Google Scholar

Dole el J, Barto J, Voglmayr H, Greilhuber J

. 2003 Nuclear DNA content and genome size of trout and human . Cytometry 51A, 127-128. Google Scholar

. 2014 A Linear-time algorithm for Gaussian and non-Gaussian trait evolution models . Syst. Biol. 63, 397-408. (doi:10.1093/sysbio/syu005) Crossref, PubMed, ISI, Google Scholar

. 2014 RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies . Bioinformatics 30, 1312-1313. (doi:10.1093/bioinformatics/btu033) Crossref, PubMed, ISI, Google Scholar

Chang J, Rabosky DL, Alfaro ME

. 2020 Estimating diversification rates on incompletely-sampled phylogenies: theoretical concerns and practical solutions . Systematic Biol. 69, 602-611. (doi:10.1093/sysbio/syz081) Crossref, PubMed, ISI, Google Scholar

. 2015 No substitute for real data: a cautionary note on the use of phylogenies from birth–death polytomy resolvers for downstream comparative analyses . Evolution 69, 3207-3216. (doi:10.1111/evo.12817) Crossref, PubMed, ISI, Google Scholar

Drori M, Rice A, Einhorn M, Chay O, Glick L, Mayrose I

. 2018 OneTwoTree: an online tool for phylogeny reconstruction . Mol. Ecol. Resour. 18, 1492-1499. (doi:10.1111/1755-0998.12927) Crossref, PubMed, ISI, Google Scholar

Li L, Stoeckert CJ, Roos DS

. 2003 OrthoMCL: identification of ortholog groups for eukaryotic genomes . Genome Res. 13, 2178-2189. (doi:10.1101/gr.1224503) Crossref, PubMed, ISI, Google Scholar

. 2013 mafft multiple sequence alignment software version 7: improvements in performance and usability . Mol. Biol. Evol. 30, 772-780. (doi:10.1093/molbev/mst010) Crossref, PubMed, ISI, Google Scholar

. 2019 Priors and posteriors in Bayesian timing of divergence analyses: the age of butterflies revisited . Syst. Biol. 0, 1-17. Google Scholar

. 2008 Phyutility: a phyloinformatics tool for trees, alignments and molecular data . Bioinformatics 24, 715-716. (doi:10.1093/bioinformatics/btm619) Crossref, PubMed, ISI, Google Scholar

. 2012 MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space . Syst. Biol. 61, 539-542. (doi:10.1093/sysbio/sys029) Crossref, PubMed, ISI, Google Scholar

. 2013 Molecular dating of phylogenies by likelihood methods: a comparison of models and a new information criterion . Mol. Phylo. Evol. 67, 436-444. (doi:10.1016/j.ympev.2013.02.008) Crossref, PubMed, ISI, Google Scholar

. 2019 ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R . Bioinformatics 35, 526-528. (doi:10.1093/bioinformatics/bty633) Crossref, PubMed, ISI, Google Scholar

. 2017 Cladogenetic and anagenetic models of chromosome number evolution: a Bayesian model averaging approach . Syst. Biol. 67, 195-215. (doi:10.1093/sysbio/syx065) Crossref, ISI, Google Scholar

Höhna S, Landis MJ, Heath TA, Boussau B, Lartillot N, Moore BR, Huelsenbeck JP, Ronquist F

. 2016 RevBayes: Bayesian phylogenetic inference using graphical models and an interactive model-specification language . Syst. Biol. 65, 726-736. (doi:10.1093/sysbio/syw021) Crossref, PubMed, ISI, Google Scholar

Rambaut A, Drummond AJ, Xie D, Baele G, Suchard MA

. 2018 Posterior summarization in Bayesian phylogenetics using Tracer 1.7 . Syst. Biol. 67, 901-904. (doi:10.1093/sysbio/syy032) Crossref, PubMed, ISI, Google Scholar

. 2012 Diversitree: comparative phylogenetic analyses of diversification in R . Methods Ecol. Evol. 3, 1084-1092. (doi:10.1111/j.2041-210X.2012.00234.x) Crossref, ISI, Google Scholar

. 2011 phytools: an R package for phylogenetic comparative biology (and other things) . Methods Ecol. Evol. 3, 217-223. (doi:10.1111/j.2041-210X.2011.00169.x) Crossref, ISI, Google Scholar

Kristensen NP, Scoble MJ, Karsholt O

. 2007 Lepidoptera phylogeny and systematics: the state of inventorying moth and butterfly diversity . Zootaxa 1668, 699-747. (doi:10.11646/zootaxa.1668.1.30) Crossref, ISI, Google Scholar

Blackmon H, Ross L, Bachtrog D

. 2016 Sex determination, sex chromosomes, and karyotype evolution in insects . J. Hered. 108, 78-93. (doi:10.1093/jhered/esw047) Crossref, PubMed, ISI, Google Scholar

Rice A, Glick L, Abadi S, Einhorn M, Kopelman NM, Salman-Minkov A, Mayzel J, Chay O, Mayrose I

. 2015 The Chromosome Counts Database (CCDB)—a community resource of plant chromosome numbers . New Phytol. 206, 19-26. (doi:10.1111/nph.13191) Crossref, PubMed, ISI, Google Scholar

Cuacos M, Franklin FC H, Heckmann S

. 2015 Atypical centromeres in plants—what they can tell us . Front. Plant. Sci. 6, 1247. (doi:10.3389/fpls.2015.00913) Crossref, PubMed, ISI, Google Scholar

Pringle EG, Baxter SW, Webster CL, Papanicolaou A, Lee SF, Jiggins CD

. 2007 Synteny and chromosome evolution in the Lepidoptera: evidence from mapping in Heliconius melpomene . Genetics 177, 417-426. (doi:10.1534/genetics.107.073122) Crossref, PubMed, ISI, Google Scholar

Leaché A. D., Banbury BL, Linkem CW, de Oca AN.-M.

2016 Phylogenomics of a rapid radiation: is chromosomal evolution linked to increased diversification in North American spiny lizards (genus Sceloporus)? BMC Evol. Biol. 16, 63. (doi:10.1186/s12862-016-0628-x) Crossref, PubMed, ISI, Google Scholar

2014 Plant speciation through chromosome instability and ploidy change: cellular mechanisms, molecular factors and evolutionary relevance . Curr. Plant Biol. 1, 10-33. (doi:10.1016/j.cpb.2014.09.002) Crossref, Google Scholar

Bush GL, Case SM, Wilson AC, Patton JL

. 1977 Rapid speciation and chromosomal evolution in mammals . Proc. Natl Acad. Sci. USA 74, 3942-3946. (doi:10.1073/pnas.74.9.3942) Crossref, PubMed, ISI, Google Scholar

. 2010 Genome size and species diversification . Evol. Biol. 37, 227-233. (doi:10.1007/s11692-010-9093-4) Crossref, PubMed, ISI, Google Scholar

Puttick MN, Clark J, Donoghue PC. J

. 2015 Size is not everything: rates of genome size evolution, not C-value, correlate with speciation in angiosperms . Proc. R. Soc. B. 282, 20152289. (doi:10.1098/rspb.2015.2289) Link, ISI, Google Scholar

Mackintosh A, Laetsch DR, Hayward A, Charlesworth B, Waterfall M, Vila R, Lohse K

. 2019 The determinants of genetic diversity in butterflies . Nat. Commun. 10, 3466. (doi:10.1038/s41467-019-11308-4) Crossref, PubMed, ISI, Google Scholar

Maddison WP, Midford PE, Otto SP

. 2007 Estimating a binary character's effect on speciation and extinction . Syst. Biol. 56, 701-710. (doi:10.1080/10635150701607033) Crossref, PubMed, ISI, Google Scholar

Davis MP, Midford PE, Maddison W

. 2013 Exploring power and parameter estimation of the BiSSE method for analyzing species diversification . BMC Evol. Biol. 13, 38. (doi:10.1186/1471-2148-13-38) Crossref, PubMed, ISI, Google Scholar

. 2016 Notes on the statistical power of the binary state speciation and extinction (BiSSE) Model . Evol. Bioinform. 12, 164-174. (doi:10.4137/EBO.S39732) Crossref, ISI, Google Scholar

. 2014 The unsolved challenge to phylogenetic correlation tests for categorical characters . Syst. Biol. 64, 127-136. (doi:10.1093/sysbio/syu070) Crossref, PubMed, ISI, Google Scholar

. 2016 Detecting hidden diversification shifts in models of trait-dependent speciation and extinction . Syst. Biol. 65, 583-601. (doi:10.1093/sysbio/syw022) Crossref, PubMed, ISI, Google Scholar

. 2015 Model inadequacy and mistaken inferences of trait-dependent speciation . Syst. Biol. 64, 340-355. (doi:10.1093/sysbio/syu131) Crossref, PubMed, ISI, Google Scholar

. 2014 Automatic detection of key innovations, rate shifts, and diversity-dependence on phylogenetic trees . PLoS ONE 9, e89543. (doi:10.1371/journal.pone.0089543) Crossref, PubMed, ISI, Google Scholar

. 2016 Past, future, and present of state-dependent models of diversification . Am. J. Bot. 103, 792-795. (doi:10.3732/ajb.1600012) Crossref, PubMed, ISI, Google Scholar

Rosenblum EB, Sarver BA. J., Brown JW, Roches Des S, Hardwick KM, Hether TD, Eastman JM, Pennell MW, Harmon LJ

. 2012 Goldilocks meets Santa Rosalia: an ephemeral speciation model explains patterns of diversification across time scales . Evol. Biol. 39, 255-261. (doi:10.1007/s11692-012-9171-x) Crossref, PubMed, ISI, Google Scholar

. 2005 Genetics and extinction . Biol. Cons. 126, 131-140. (doi:10.1016/j.biocon.2005.05.002) Crossref, ISI, Google Scholar

Mérot C, Salazar C, Merrill RM, Jiggins CD, Joron M

. 2017 What shapes the continuum of reproductive isolation? Lessons from Heliconius butterflies . Proc. R. Soc. B. 284, 20170335. (doi:10.1098/rspb.2017.0335) Link, ISI, Google Scholar

Kandul NP, Lukhtanov VA, Dantchenko AV, Coleman JWS, Sekercioglu CH, Haig D, Pierce NE

. 2004 Phylogeny of Agrodiaetus Hübner 1822 (Lepidoptera: Lycaenidae) inferred from mtDNA sequences of COI and COII and nuclear sequences of EF1-alpha: karyotype diversification and species radiation . Syst. Biol. 53, 278-298. (doi:10.1080/10635150490423692) Crossref, PubMed, ISI, Google Scholar

Kandul NP, Lukhtanov VA, Pierce NE

. 2007 Karyotypic diversity and speciation in Agrodiaetus butterflies . Evolution 61, 546-559. (doi:10.1111/j.1558-5646.2007.00046.x) Crossref, PubMed, ISI, Google Scholar

Lukhtanov VA, Shapoval NA, Anokhin BA, Saifitdinova AF, Kuznetsova VG

. 2015 Homoploid hybrid speciation and genome evolution via chromosome sorting . P. R. Soc. B. 282, 20150157. (doi:10.1098/rspb.2015.0157) Link, ISI, Google Scholar

Šíchová J, Ohno M, Dinca V, Watanabe M, Sahara K, Marec F

. 2016 Fissions, fusions, and translocations shaped the karyotype and multiple sex chromosome constitution of the northeast-Asian wood white butterfly, Leptidea amurensis . Biol. J. Linn. Soc. 118, 457-471. (doi:10.1111/bij.12756) Crossref, ISI, Google Scholar

Lukhtanov VA, Dinca V, Talavera G, Vila R

. 2011 Unprecedented within-species chromosome number cline in the wood white butterfly Leptidea sinapis and its significance for karyotype evolution and speciation . BMC Evol. Biol. 11, 109. (doi:10.1186/1471-2148-11-109) Crossref, PubMed, ISI, Google Scholar

. 2015 The butterfly plant arms-race escalated by gene and genome duplications . Proc. Natl Acad. Sci. USA 112, 8362-8366. (doi:10.1073/pnas.1503926112) Crossref, PubMed, ISI, Google Scholar

Pardo-Diaz C, Salazar C, Baxter SW, Merot C, Figueiredo-Ready W, Joron M, Mcmillan WO, Jiggins CD

. 2012 Adaptive introgression across species boundaries in Heliconius butterflies . PLoS Genet. 8, e1002752. (doi:10.1371/journal.pgen.1002752) Crossref, PubMed, ISI, Google Scholar

. 2011 Chromosomal rearrangements maintain a polymorphic supergene controlling butterfly mimicry . Nature 477, 203-206. (doi:10.1038/nature10341) Crossref, PubMed, ISI, Google Scholar

Kozak KM, Wahlberg N, Neild AFE, Dasmahapatra KK, Mallet J, Jiggins CD

. 2015 Multilocus species trees show the recent adaptive radiation of the mimetic Heliconius butterflies . Syst. Biol. 64, 505-524. (doi:10.1093/sysbio/syv007) Crossref, PubMed, ISI, Google Scholar

Saura A, Schoultz Von B, Saura AO, Brown KSJ

. 2013 Chromosome evolution in Neotropical butterflies . Hereditas 150, 26-37. (doi:10.1111/j.1601-5223.2013.00008.x) Crossref, PubMed, ISI, Google Scholar

Kulmuni J, Butlin RK, Lucek K, Savolainen V, Westram AM

. 2020 Towards the completion of speciation: the evolution of further reproductive isolation beyond the first barriers . Phil. Trans. R. Soc. B 375, 20190528. (doi:10.1098/rstb.2019.0528) Link, ISI, Google Scholar

Ahola V, Wahlberg N, Frilander MJ

. 2017 Butterfly genomics: insights from the genome of Melitaea cinxia . Ann. Zool. Fennici 54, 275-291. (doi:10.5735/086.054.0123) Crossref, ISI, Google Scholar


15.6: Varying Rates of Speciation - Biology

A subscription to J o VE is required to view this content. You will only be able to see the first 20 seconds .

The JoVE video player is compatible with HTML5 and Adobe Flash. Older browsers that do not support HTML5 and the H.264 video codec will still use a Flash-based video player. We recommend downloading the newest version of Flash here, but we support all versions 10 and above.

If that doesn't help, please let us know.

The process of speciation is a transition over a long period of evolutionary time during which the two species continue to interact.

For example, after the isolation of these two lake fish populations, reproductive barriers may weaken and gene flow may come to occur again, fusing the two populations into one again.

If the offspring are less fit than the parents, the two populations will continue to diverge, a process called reinforcement. However, if the offspring are more fit than the parents, they will continue to be produced, a process called stability.

These mechanisms along with environmental conditions will effect the rates at which speciation occurs.

Some species evolve in small gradual steps, like these two fish populations, slowly developing different cryptic patterns or rapidly and remain unchanged for long periods of time.

30.3: Speciation Rates

Overview

Speciation usually occurs over a long evolutionary time scale, during which the species may be isolated or continue to interact. If two emerging species start to interbreed, reproductive barriers may be weak, and gene flow can occur again. At this point, the selection of hybrids across the two populations may either stabilize the newly mixed group into a single population or reinforce the distinction between them as new species. Speciation may occur gradually or rapidly, and in some cases is punctuated between long periods without change followed by rapid rates of speciation.

Reconnection of Populations

In cases of speciation where two or more populations have become isolated for some time, they may reconnect. For example, in long periods of drought or climate change, large lakes can be split into many smaller lakes, isolating the inhabitants. The vast species diversity of African cichlid fish was fueled, in part, by periods of such population fragmentation. When the conditions changed, and fragmented lakes merged again, isolated populations got back into contact.

When reconnection occurs, if pre-zygotic reproductive barriers are weak, individuals from the two different populations may begin to reproduce. If the fitness of the hybrid offspring is higher or unchanged compared to the parents, the populations can integrate and merge. This process is referred to as stability. However, if the hybrid offspring are less fit than non-mixed offspring from the parent populations or pre-zygotic barriers to reproduction are strengthened with time, the two populations will continue to diverge even in sympatry&mdasha process known as reinforcement. In the cichlid fishes, many new lineages and species were likely generated in this way.

Rates of Evolution and Speciation

Species may evolve at different rates depending on generation time, the strength of selection pressures and specific environmental conditions. Usually, change happens slowly, with alterations occurring in small increments over time until a new species emerges that no longer interbreeds with other species. This concept is known as phyletic gradualism. For example, if birds with slightly longer beaks can dig deeper into trees for grubs, the entire population may skew towards longer beaks over time, and eventually, become distinct from their short-beaked relatives.

However, it is also possible for species to change relatively rapidly. This ties into the theory of punctuated equilibrium that states that species may undergo spurts of rapid evolutionary change, followed by long periods of remaining relatively unchanged. Support for the theory comes from the observation that some fossil lineages appear to change little for long periods of time, then show rapid change in the fossil record.

The butterfly genus Heliconius shows strong selection to preserve color pattern due to selection for mimicry, and this generally keeps species stable even in sympatry with closely related sister species. However, rapid speciation can occur in the event of mutation or hybridization which produces a novel &ldquofit&rdquo phenotype. Overall evolution and speciation can proceed in various ways and different time scales.

Schluter, Dolph, and Gina L. Conte. &ldquoGenetics and Ecological Speciation.&rdquo Proceedings of the National Academy of Sciences 106, no. Supplement 1 (June 16, 2009): 9955&ndash62. [Source]

Jablonski, David. &ldquoApproaches to Macroevolution: 1. General Concepts and Origin of Variation.&rdquo Evolutionary Biology 44, no. 4 (2017): 427&ndash50. [Source]

Brawand, David, Catherine E. Wagner, Yang I. Li, Milan Malinsky, Irene Keller, Shaohua Fan, Oleg Simakov, et al. &ldquoThe Genomic Substrate for Adaptive Radiation in African Cichlid Fish.&rdquo Nature 513, no. 7518 (September 18, 2014): 375&ndash81. [Source]


Acknowledgements

We thank M. Grundler for statistical and coding advice, and M. Venzon and A. Noonan for assistance with dataset assembly. We are grateful to the many institutions that curate the primary biodiversity data that underlie several of our analyses (see Supplementary Table 6). This research was carried out using computational resources and services provided by Advanced Research Computing at the University of Michigan, Ann Arbor. This work was supported in part by NSF grant DEB-1256330 (D.L.R.), an NSF DDIG grant to J.C. (DEB-1601830), an Encyclopedia of Life Rubenstein Fellowship to J.C. (EOL-33066-13) and by a Fellowship from the David and Lucile Packard Foundation (D.L.R.). P.F.C. was funded by a Gaylord Donnelley Postdoctoral Environment Fellowship (Yale) and through the ARC Centre of Excellence for Coral Reef Studies. We thank J. Johnson for creating the fish images in Fig. 3 and Extended Data Fig. 7.

Reviewer information

Nature thanks O. Bininda-Emonds, O. Seehausen and the other anonymous reviewer(s) for their contribution to the peer review of this work.


The MuSSE model

MuSSE is a straightforward extension of BiSSE to discrete traits with more than two states. Some characters are not naturally binary (e.g. mating systems, diets or count data), and MuSSE allows these to be treated naturally. This method has been used to examine the effect of diet (faunivore, folivore, frugivore) in primates ( Gómez & Verdú 2012 ). Alternatively, MuSSE can be used to disentangle the relative importance of two or more traits to diversification.

Suppose that we have a trait that takes values 1,2,…,k that might influence speciation and/or extinction. Using the notation and approach of Maddison, Midford & Otto (2007) , let lineages in state i speciate at rate λi, go extinct at rate μi and transition to state ji at rate qij. For k states, there are k speciation rates, k extinction rates and k(k−1) transition rates.


Minimal effects of latitude on present-day speciation rates in New World birds

The tropics contain far greater numbers of species than temperate regions, suggesting that rates of species formation might differ systematically between tropical and non-tropical areas. We tested this hypothesis by reconstructing the history of speciation in New World (NW) land birds using BAMM, a Bayesian framework for modelling complex evolutionary dynamics on phylogenetic trees. We estimated marginal distributions of present-day speciation rates for each of 2571 species of birds. The present-day rate of speciation varies approximately 30-fold across NW birds, but there is no difference in the rate distributions for tropical and temperate taxa. Using macroevolutionary cohort analysis, we demonstrate that clades with high tropical membership do not produce species more rapidly than temperate clades. For nearly any value of present-day speciation rate, there are far more species in the tropics than the temperate zone. Any effects of latitude on speciation rate are marginal in comparison to the dramatic variation in rates among clades.

1. Introduction

Many groups of organisms are characterized by a striking latitudinal gradient in species diversity, with many more species occurring in tropical regions than in temperate regions [1–4]. Despite decades of study, the causes of this latitudinal diversity gradient (LDG) remain poorly understood. Many hypotheses for the LDG have been proposed that ultimately involve differential rates of species formation and/or extinction in the tropics relative to temperate regions [5,6]. Hence, the presence or the absence of a latitudinal gradient in diversification rates can support or reject a number of specific models for the LDG, even if the precise mechanisms underlying rate variation remain unknown.

Some recent studies have suggested that rates of species diversification vary systematically between tropical and temperate regions, although these studies have reached contrasting conclusions [7–10]. Others have found little evidence for latitudinal variation in diversification rates [11,12]. At least in part, these discrepancies may reflect taxon-specific differences in the relationship between latitude and diversification. However, it is also true that we face many challenges in the reconstruction of historical diversification rates using phylogenetic and distributional data from extant species. One challenge involves the inference of extinction rates. Even when all assumptions of the inference model used for reconstructing extinction rates are satisfied, confidence intervals on extinction rates are large [13,14]. When assumptions of the inference model are violated, extinction rate estimates can range from biased to nonsensical [15]. Another challenge involves the accuracy of historical biogeographic reconstructions: it is difficult to study the history of diversification rates with respect to geographical region, because—in the absence of a detailed fossil record—the only biogeographic information to which we have direct access consists of present-day distributions of species. Recent studies have demonstrated the challenges in reconstructing historical geographical distributions, even at the coarse scales of ‘tropical’ and ‘temperate’ [16].

In this study, we describe the latitudinal gradient in present-day speciation rates across all New World (NW) land birds. The LDG in species richness for NW birds is extreme [17–19], with many more species occurring in tropical South and Central America relative to southern South America and North America (figure 1). We focus explicitly on ‘recent’, or ‘present-day’ rates of speciation for several reasons. First, speciation rates can be estimated with much greater confidence than extinction rates, even when extinction rates vary among lineages [13,20]. The reason for this is simple, if not widely appreciated. Extinction events are unobserved quantities, and any pattern on a time-calibrated phylogeny is consistent, in principle, with high extinction as well as zero extinction. This is not true for speciation rates, because the density of nodes near the tips of a reconstructed phylogenetic tree is an absolute count of the minimum number of speciation events that could have occurred: to observe a node, a speciation event must have occurred. The minimum number of speciation events that could have occurred across any portion of a phylogenetic tree must always be greater than or equal to the corresponding minimum number of extinction events (typically zero). Narrower bounds on plausible numbers of speciation events mean that speciation rates will always be inferred with greater accuracy than extinction rates in the absence of fossils.

Figure 1. Latitudinal gradient in the land birds of the NW (breeding range). The true latitudinal gradient in species richness (grey curve) is very similar to the latitudinal gradient across the set of taxa present in the phylogenetic dataset (black curve). The latitudinal diversity in passerine birds (n = 2260 species in total) is driven almost entirely by two large clades: the suboscine passerines and the tanagers. These clades are largely restricted to the NW tropics yet highly diverse. When we consider the gradient in passerines after removing these two clades (blue), the tropics no longer contain more species than the temperate zone. (Online version in colour.)

A more important reason for focusing on present-day speciation rates is that it enables robust tests of alternative hypotheses for the LDG without requiring the use of assumption-laden methods for reconstructing the historical geography of specific lineages [16,21]. Many candidate explanations for the LDG predict that present-day speciation rates should be higher in species from the tropics relative to those that inhabit the temperate zone. Mittlebach et al. [5] reviewed evolutionary causes of the LDG, identifying at least seven distinct hypotheses that predict faster present-day rates of speciation in the tropics. For example, several hypotheses invoke relationships between evolutionary speed and temperature [6] and its kinetic effects on speciation rate [22]. Others have proposed that the strength of biotic interactions in the tropics might drive faster speciation [23]. Another class of explanations holds that biogeographic processes in tropical regions have led to faster speciation rates [24,25]. The general hypothesis of ‘speciation rate’ is thus an omnibus class of explanations that includes many potential mechanisms, all of which predict faster present-day rates of speciation in the tropics relative to temperate regions [5]. We addressed these hypotheses by focusing on a simple question: what are the distributions of present-day speciation rates for tropical and temperate land birds of the NW?

2. Material and methods

(a) Phylogenetic and latitudinal data

We used the phylogenetic framework from [11] to study the relationship between speciation rates and latitude. The Jetz et al. dataset (JEA) consists of two distributions of phylogenetic trees: one constructed with the higher level Hackett backbone topology [26], and a second distribution constructed using the Ericson backbone topology [27]. The phylogenetic positions of 33% of all species in the original JEA study were imputed subject to taxonomic constraints we eliminated these species from the Hackett and Ericson distributions of phylogenies, as no genetic data were available to guide the placement of these taxa. We then computed the maximum clade credibility (MCC) tree for the distributions of both the Hackett and Ericson phylogenies, where each phylogeny included the 6670 taxa whose placement used at least some genetic data. These two trees—the MCC Hackett and Ericson phylogenies—form the core of all analyses described below. Hereafter, we refer to these MCC trees as the ‘Hackett’ and ‘Ericson’ phylogenies. Species distributional data were acquired for over 10 000 species from BirdLife International as GIS shapefiles [28]. Minimum, maximum and centroid latitude were measured from these distributions using the sp [29] and rgeos [30] packages in R. Each species distribution was tested for its intersection with major continents using the rgeos package.

(b) Analyses with BAMM

We used BAMM to study patterns of speciation rate variation across the avian phylogenies. BAMM is a software program that uses reversible jump Markov chain Monte Carlo (RJMCMC) to quantify complex patterns of diversification rate variation on phylogenetic trees [20,31,32]. BAMM can estimate posterior distributions of evolutionary rates at any point in time along the branches of phylogenetic trees. BAMM does not estimate a single ‘best’ set of evolutionary rate shifts, but simulates a posterior distribution of evolutionary rate shift configurations, where each shift configuration is sampled in proportion to its posterior probability. Each evolutionary rate shift in BAMM creates a ‘cohort’ of taxa that share common evolutionary parameters of speciation and extinction by definition, all species in a cohort have identical diversification rates at any point in time. At the end of a BAMM run, posterior distributions of present-day speciation rates can be estimated for each individual taxon, by taking the marginal density of rates at the tips of the trees across all sampled rate shift configurations [33]. Because we are averaging speciation rates across multiple rate shift configurations, all taxa can potentially have a unique rate of speciation.

Tip rates computed in this fashion are essentially a predictive estimate of the present-day rate of speciation for every species in the tree. Marginal rates computed for individual species can potentially track rate variation that would be overlooked if we focused solely on rates inferred under the overall best shift configuration [31]. Consider a scenario where a ‘background’ speciation rate increases to a ‘fast’ speciation rate, but where the rate increase is mediated by a nested sequence of minor evolutionary innovations that occur along a set of adjacent ancestor-descendant branches in a phylogenetic tree. The effect of any single innovation on speciation rate might be relatively small, but a clade that inherits all the innovations together might have a greatly increased rate of speciation. However, an early diverging lineage might only share one or several such innovations and would thus have a lower speciation rate. BAMM can track such variation with a single rate shift, if the posterior shift density along branches is proportional to the cumulative number of minor innovations that have occurred. The marginal rates for individual species would reflect this variation and allow early diverging lineages to have rates that are intermediate between the background and fast rates.

Because incomplete taxon sampling can bias diversification analyses [34,35], we addressed incomplete sampling by including family-specific sampling fractions directly into our diversification analysis. To correct for sampling at the family level, we used a taxonomic classification for all birds to estimate the percentage of taxa from each family-level clade that were not included in the analysis this approach has been described previously in an analysis of fish diversification [32]. Species were assigned to families using the modified Birdlife taxonomy as described in Jetz et al. [11].

We analysed the 6670 taxon Hackett and Ericson phylogenies with BAMM, performing two separate runs of 250 million generations of RJMCMC sampling on each phylogeny. We placed exponential priors with mean values of 1.0 on all rate parameters, and an exponential hyperprior with rate 0.02 on the rate parameter of the Poisson distribution governing the number of diversification shifts across the phylogeny. We placed a normal prior with a mean of 0.0 and standard deviation of 0.05 on the exponential change parameter for the speciation rate with respect to time. We discarded the first 10% of each run as ‘burn-in’ and tested the distribution for convergence by computing the effective sample size in the number of evolutionary rate regimes in the dataset.

All BAMM analyses were performed on the avian phylogeny of 6670 species (both Hackett and Erison topologies), with the analytical family-level correction for incomplete taxon sampling. For all subsequent analyses with BAMM output, we pruned the trees to include only NW land birds (2571 species). This included only those taxa with breeding ranges in continental North or South America, and we also excluded all taxa from the following aquatic or semi-aquatic orders: Anseriformes, Charadriiformes, Gaviiformes, Pelecaniformes, Phaethontiformes, Phoenicopteriformes, Podicipediformes, Procellariiformes, Sphenisciformes and Suliformes.

(c) Analysis of the relationship between speciation rate and latitude

We estimated the marginal distribution of present-day speciation rates for each taxon for both Hackett and Ericson phylogenies. We then merged these distributions by computing the overall mean speciation rate across both topologies, yielding a single average rate of speciation. We compared distributions of species-level rates for taxa with centroid midpoints in the tropics and temperate zone. If speciation rates are faster in the tropics relative to the temperate zone, the distribution of species-level speciation rates should be right-shifted relative to the corresponding temperate zone rate distribution.

We also tested the relationship between latitude and speciation rate using statistically independent cohorts of lineages from BAMM analyses, where each cohort represents a set of lineages that are assigned to the same dynamic rate class [31]. Rates for any given cohort are, by definition, statistically independent of those for all other cohorts. The macroevolutionary cohort matrix [31] describes the pairwise matrix of correlations in evolutionary rates that are attributable to the BAMM model itself. Cohorts are not merely a simple grouping of lineages with similar rate dynamics: they are lineages that are inferred to share an unobserved organismal trait or geographical state that results in identical diversification dynamics for all lineages possessing the feature. Lineages can only belong to the same cohort by virtue of common ancestry: clades that have converged on similar diversification rate dynamics cannot be part of the same cohort. For each sample in the posterior set of macroevolutionary rate shift configurations simulated using BAMM, we computed: (i) the fraction of taxa in the cohort that are from the tropics, and (ii) the latitudinal midpoint of all taxa in the cohort. We tested whether the speciation rate of each cohort was associated with either of these metrics of ‘tropical-ness'. If latitude has a consistent effect on speciation rate, then more tropical cohorts should have faster rates of speciation than temperate cohorts.

(d) Analyses with time-constant rate of speciation

In a seminal paper, Weir & Schluter [7] found that present-day speciation and extinction rates were faster in the temperate zone relative to the tropics for NW birds and mammals. In the full BAMM model, each macroevolutionary rate regime includes a time-varying speciation process, where the rate of speciation varies through time using an exponential change function [20]. We repeated the analyses above but constrained speciation rates to be constant through time within rate regimes, in order to compare our results more directly with those of Weir & Schluter [7]. To constrain rates through time, we fixed the value of the exponential change parameter for speciation rate variation to zero during the MCMC simulation. After constraining the exponential change parameter, the BAMM model is similar to the MEDUSA model [36], because both approaches assume that phylogenies include a mixture of distinct constant-rate diversification partitions.

3. Results

(a) BAMM results

All BAMM runs had effective sample sizes in excess of 900 for the number of rate shifts. Independent runs had nearly identical distributions of log-likelihoods: we computed the 0.05, 0.10, 0.15 … 0.85, 0.90 and 0.95 quantiles of the distribution of log-likelihoods for the Ericson and Hackett runs the slope of the relationship between quantiles from the two Hackett runs was 0.992, and the slope of the relationship between quantiles for the two Ericson runs was 0.990. Median log-likelihoods were nearly identical for the Hackett runs (−20 314 and −20 317) as well as for the Ericson runs (−20 579 and −20 581). Log-likelihoods from the Hackett and Ericson phylogenies cannot be compared, as the trees are not identical.

Within the two Hackett runs, speciation rate estimates at the tips of the trees were highly correlated with each other (Pearson r = 0.996), and the same was true of the two Ericson runs (r = 0.998). The correlation between branch-specific marginal shift probabilities was 0.986 for the two Hackett runs, and 0.976 for the two Ericson runs. These results imply that the Ericson and Hackett runs converged on the similar posterior distributions of macroevolutionary rate shift configurations. Finally, tip-specific rates for the Hackett runs were highly correlated with those of the Ericson runs (r = 0.90 electronic supplementary material, figure S1). This indicates that, despite the overall structural differences between these phylogenies, the overall taxon-specific rate estimates are relatively robust to uncertainty about phylogenetic tree topology.

Comparisons of posterior and prior distributions on the number of rate shifts provide strong support for highly heterogeneous diversification dynamics across birds (electronic supplementary material, figure S2). Posterior distributions of the number of macroevolutionary rate regimes across the full Hackett and Ericson trees were nearly identical: the maximum a posteriori probability estimate of the number of rate shifts for the Hackett tree was 68, versus 69 for the Ericson tree. The 95% CI on the number of rate shifts were nearly identical for these two datasets: 58–79 for the Hackett dataset, and 59–79 for the Ericson dataset. Because the prior distribution is identical for both sets of analyses, statistical support for complex rate variation is nearly identical for Hackett and Ericson trees hence, we summarize only the results for the Hackett tree here. There is no measurable overlap between prior and posterior distributions for these data (electronic supplementary material, figure S2): the observed posterior distribution of the number of shifts is substantially right-shifted relative to the prior distribution. All observed rate shift counts in the posterior have prior probabilities that are effectively equal to zero, indicating that the data contain very strong evidence for heterogeneous speciation dynamics.

(b) Rate distributions for tropical and temperate taxa

We estimated marginal distributions of present-day rates of species formation for all 2571 species of NW land birds in the phylogenetic dataset (figure 2a) these per-taxon rates range from 0.04 to 1.11 new species per million years (Myr). There is no trend in the distribution of speciation rates with respect to latitude, but all latitudes include a mixture of lineages with relatively fast and slow rates of speciation (figure 2b). Latitude is structured phylogenetically: some large clades, such as the suboscine passerines (flycatchers, ovenbirds, antbirds, cotingas, manakins) are largely restricted to the NW tropics. However, the suboscines comprise a mixture of lineages with slow, intermediate and fast speciation rates (figure 2a). To a first approximation, the latitudinal gradient in species richness for NW passerine birds is driven by just two clades with many species and few temperate representatives: the suboscines and the oscine tanagers (figures 1 and 2a).

Figure 2. Latitudinal range and present-day speciation rate for NW land birds. (a) Latitudinal extent of breeding range for each of 2571 NW land birds (horizontal lines) the phylogenetic tree from [11] is shown for reference. Line colour indicates present-day speciation rate for each taxon. Tropical niche conservatism is clearly visible as blocks of related taxa that generally fail to extend northwards out of the tropics. Speciation rates vary widely among clades, but tropical groups (e.g. the suboscine passerines and tanagers) do not have faster rates of speciation than clades with high temperate zone representation. (b) Quantiles (grey) and median (black) of the distribution of speciation rates with respect to latitude.

Overall, there is a weak correlation between the absolute centroid midpoint of each species’ breeding range and the corresponding rate of speciation (Pearson r = 0.046, p = 0.02 electronic supplementary material, figure S3). Median values of speciation rate across all temperate and tropical lineages are nearly identical (tropical: 0.139 temperate 0.140), although the means are slightly higher for temperate lineages (0.169 versus 0.154 t-test: p = 0.024).

If faster speciation rates in the tropics generate the LDG, the overall individual-level speciation rate distribution for the tropics should be right-shifted relative to the corresponding temperate zone distribution when visualized using a speciation-percentile plot (figure 3a). This would indicate that tropical species have faster rates than temperate regions for a given distributional percentile. If speciation rates are faster in the temperate region, as predicted by the ‘faster turnover’ hypothesis [7], we should find the tropical distribution left-shifted relative to the temperate distribution (figure 3a). We found that the distributions of speciation rates for tropical (n = 1948) and non-tropical (n = 623) taxa were virtually identical (figure 3b), a result that holds across both Ericson and Hackett phylogenies (electronic supplementary material, figure S4). Both distributions include many lineages with fast and slow rates of speciation, but there is a remarkable overall correspondence between these rate distributions.

Figure 3. Speciation rate distributions for tropical and temperate taxa are nearly identical. (a) Predicted rank-ordered plots of speciation rates for tropical (orange) and temperate (blue) taxa under several hypotheses for the LDG. If speciation is faster in the tropics, rate distributions for tropical taxa should be right-shifted or slope-shifted relative to those of temperate taxa. If speciation rates are faster at high latitudes, as predicted by the faster turnover hypothesis, tropical rates should be left-shifted. (b) Observed rate distributions for tropical (n = 1948) and temperate (n = 643) taxa. (c) Frequency distribution of speciation rates for tropical and temperate taxa. For most values of speciation rate, there are more tropical than temperate species, indicating that the large number of tropical species is not driven by an excess of fast-speciating lineages.

We tabulated the frequency distribution of speciation rates for tropical and non-tropical taxa (figure 3c). For any given value of speciation rate, there are many more species in the tropics relative to the temperate zone. For example, if we consider only those species with speciation rates between 0.09 and 0.13 lineages Myr −1 , we find 146 non-tropical species and 581 tropical species. For the median value of speciation observed in non-tropical lineages (0.140), we estimate that there are approximately 3.60 times more species in the tropics with this same speciation rate. This number accords surprisingly well with the overall ratio of tropical to temperate land birds in the NW (Ntropics/Ntemperate = 4.01). These results are robust across both passerine and non-passerine lineages (electronic supplementary material, figures S3 and S5).

(c) Macroevolutionary cohort analysis

Each rate shift in a BAMM analysis defines a cohort of lineages that share a common set of macroevolutionary rate parameters. An illustrative example of cohorts identified through BAMM analysis is shown in the electronic supplementary material, figure S6. We computed the fraction of taxa from each cohort that were centered in the tropics if speciation rates are faster in tropical regions, cohorts with greater percentages of tropical taxa should have faster rates of speciation. We also tested the relationship between the mean latitude for all taxa assigned to a cohort and the present-day rate of speciation for the cohort.

Individual cohorts vary widely in their fraction of tropical taxa: some cohorts are nearly equal mixtures of tropical and temperate species, but many large cohorts—such as the neotropical tanagers (figure 2)—are almost exclusively tropical. Despite this variation, there is no overall relationship between the fraction of tropical taxa and cohort speciation rate (figure 4a 95% CI on distribution of correlations: −0.19 to 0.31 median r = 0.06). Likewise, the latitudinal midpoint of each cohort is not associated with speciation rate (figure 4b: 95% CI on distribution of correlations: −0.25 to 0.25 median r = −0.01). The electronic supplementary material, figure S7 shows the distribution of correlations between speciation rate, latitude and the fraction of tropical species for all samples from the posterior distribution simulated with BAMM. Electronic supplementary material, figure S8 demonstrates that the independence assumption that underlies our cohort analyses is reasonable for these data. Our observation that some major clades (e.g. suboscines figure 2) and macroevolutionary cohorts (figure 4) are largely tropical yet show no evidence for accelerated speciation provides strong evidence against the hypothesis that the LDG is caused by latitudinal variation in speciation rates.

Figure 4. Speciation rates for macroevolutionary cohorts as a function of the percentage of tropical species (a) and the mean latitude (b) of all species in each cohort. Macroevolutionary cohorts are statistically independent clades (potentially paraphyletic) that are inferred to share common evolutionary rate dynamics. Speciation rate is uncorrelated with both metrics of ‘tropical-ness'. Results are shown for the best macroevolutionary shift configuration identified with BAMM results for the full posterior are shown in the electronic supplementary material, figure S7. Point size is proportional to the number of taxa in each cohort.

(d) Constant speciation through time

When we constrain our analyses such that speciation rates do not vary through time, we find statistical support for the faster turnover hypothesis [7]. The median speciation rate for temperate taxa was 0.21 lineages Myr −1 , versus 0.17 lineages Myr −1 for temperate taxa. Clearly, both tropical and temperate taxa comprise a mixture of fast- and slow-speciating lineages, even with the constant-rate constraint. However, there is a shift in the rate distributions under the constant rate model (figure 5): proportionately more temperate taxa have faster rates of speciation, accounting for the overall difference in median rates. When we relax the assumption of constant rates through time, the rate distributions for tropical and temperate taxa are effectively identical (figures 3 and 5 electronic supplementary material, figure S9).

Figure 5. Speciation rates are faster in the temperate zone when speciation rates are constrained to be constant in time. Frequency distributions are kernel density estimates for tropical and temperate taxa, inferred with the constraint that speciation rates do not vary through time. There is a clear increase in the proportion of ‘fast-speciation’ temperate taxa relative to the tropics. Results presented in figures 2, 3 and 4 are based on the more general model that allows speciation rates to vary through time. See the electronic supplementary material, figure S9 for explicit comparison with the time-variable model.

4. Discussion

Despite great variation in the rate of speciation across the land birds of the NW, we find a striking similarity in the speciation rate distributions for taxa from tropical and temperate regions (figure 3b,c). Even if we ultimately find a slight excess of fast-speciating lineages in either tropical or temperate regions, our reconstructed rate distributions (figure 3) indicate that the distribution of speciation rates is largely identical for most taxa. For any given value of speciation rate, there are more species in the tropics than in the temperate zone, and this result is not expected under any hypothesis that links speciation rates to high tropical diversity. Using macroevolutionary cohort analysis, we showed that clades with proportionately more tropical taxa do not speciate at faster rates than clades with lower tropical representation.

Our results imply that diversity-independent variation in speciation rate is unlikely to be a primary cause of the latitudinal gradient in species richness for this group of organisms. As such, our results—at least for NW birds—reject a broad class of evolutionary mechanisms for the LDG that involve variation in speciation rates [5], including the effects of temperature on speciation rates [6,37], greater capacity for allopatric speciation in tropical organisms [5] and the effects of biotic specialization on reproductive isolation [38]. The results here are based on a parametric model of speciation and extinction [20] but are nonetheless similar in broad outline to those reported using the ‘DR’ statistic, a weighted path measure of node density along the branches of a phylogenetic tree [11,39].

It is possible that tropical and temperate regions differ in levels of cryptic diversity, but this cannot drive the results presented here: downward biases in speciation estimates owing to yet-undescribed tropical diversity can only apply to yet-undescribed features of the latitudinal diversity curve, and our dataset already encompasses a substantial LDG for birds (figure 1). Thus, even if there is proportionately more undescribed taxonomic diversity in the tropics, our results remain valid as an explanation for the known LDG (figure 1).

It is also possible that revisions to the phylogenetic framework we have used here will influence the rate distributions presented here. In particular, there is emerging evidence that the Passeriformes are substantially younger than suggested by the JEA phylogenies. In our analyses, passerines—which account for approximately 55% of avian diversity—have crown ages of 66.8 and 73.3 Myr for the Hackett and Ericson backbones, respectively. Using complete genomes for 48 bird species, Jarvis et al. [40] estimated a crown age for Passeriformes that was approximately 30 Myr younger. This age discrepancy would affect our estimates of speciation rates. If the dates reported in [40] are reasonably correct, speciation rates for passerine birds are almost certainly faster than those reported here. However, we presently have no reason to expect these biases to act directionally with respect to latitude.

All latitudinal regions contain mixtures of taxa from fast- and slow-speciation clades (figure 2). This rate heterogeneity has important implications for the study of geographical variation in speciation rates, because it is clear that there is no single ‘tropical’ or ‘temperate’ rate of speciation. Several models for studying the effects of traits or geography on diversification assume that rates are identical for all lineages possessing a particular character state or inhabiting a similar region [7,14,21], but it is clear that speciation rates vary widely among lineages within a given geographical region. State-dependent models of diversification are known to be sensitive to violations of this assumption. We do not fully understand the consequences of violating these assumptions, but unaccommodated rate heterogeneity can result in inflated Type I error rates [41,42] and severely biased ancestral state estimates [43].

A previous study suggested that rates of species turnover in NW birds were faster in the temperate zone [7], mediated by faster rates of both speciation and extinction at high latitudes. The statistical model used in their analyses assumed that evolutionary rates varied with respect to latitude but did not address the possibility that rates vary predictably through time. Our BAMM analyses recover the same general pattern they reported, but only after we constrained speciation rates to be constant in time (figure 5).

Relaxing this assumption yields latitudinal invariance in the rate of speciation (figure 3), consistent with the suggestion that tropical and temperate clades might vary predictably in the rate at which speciation changes through time, even if present-day rates do not differ among regions [39]. If rates are constrained to be time-constant, the present-day estimate of speciation rate should be more of a time-averaged rate, rather than a true estimate of the present-day rate. Hence, we expect that the difference between these analyses (figure 5) may reflect the possibility that some temperate clades underwent faster episodes of speciation in the past but that these rates have decelerated towards the present. This is consistent with the observation that some predominantly temperate zone clades, such as Dendroica/Setophaga wood-warblers (Parulidae), have undergone explosive bursts of speciation followed by pronounced temporal decelerations towards the present [44,45].

It is also possible that, at least in part, the general lack of relationship between speciation rate and latitude reflects relatively low power to identify clades or cohorts with shifts to lower diversification rates. In addition, the power of BAMM and other methods to identify diversification rate heterogeneity on large phylogenetic trees remains poorly known. Thus, it is possible that our analyses have failed to detect a number of temperate lineages that have undergone diversification rate declines. However, macroevolutionary cohort analyses (figure 4) argue against low power as an explanation for these results.

Because we analysed present-day rates of speciation, it remains possible that ecological modulation of the rate of speciation through time, through diversity-dependent feedback mechanisms, is the primary cause of the LDG [39,46]. However, our results do not enable us to distinguish between diversity-dependence and other potential causes of the LDG. We did not assess the relationship between extinction and latitude, and it is possible that net diversification rates are faster in the tropics. Studies comparing species richness of tropical and temperate avian clades have yielded mixed results [10,12], though we find it interesting that the tropical suboscine clade has approximately the same diversity as the oscines (figure 2b). If systematic differences in net diversification rates underlie the LDG in passerines, we would expect the suboscines, which are largely restricted to the neotropics, to have greater species richness than the oscines.

It is also possible that the LDG reflects greater ‘evolutionary time’ for diversity to accumulate in tropical regions [47–49]. However, at least two observations argue against this, at least for the passerines. First, the suboscines have been present in the NW for at least 10 Myr longer than oscine lineages [39,50,51], but—in spite of this age difference—the clades are roughly equal in species richness. Second, the LDG within the oscine passerines is not consistent with a greater age for tropical clades. It is true that oscines on the whole are characterized by higher tropical diversity [39], but this is almost entirely driven by the tanagers, a single tropical clade, nested within a set of largely temperate oscine lineages [16,39,52].

As noted by other researchers [11,52–54], the radiation of modern birds is characterized by considerable variation in diversification rates. We are only beginning to understand the complex relationships between biotic and abiotic factors that lead to clade-specific differences in diversification, but our results suggest that such factors have profoundly shaped the diversity of living birds independent of their relationship with latitude.


15.6: Varying Rates of Speciation - Biology

CHAPTER 14: Speciation and Extinction

Much of the material cited in this lecture outline came from your textbook. It is highly beneficial to read these chapters carefully before your final exam.

You have open access (no log-in or password needed) to instructional materials on the Text web site. Select "Resources" from the upper left of the page and select the text chapter you want.

Moodle

You may also ask questions and see answers to your classmates' questions in Moodle in the "Talk to Ed" forum.

Objectives:

The content of today's lecture will help you complete these assignments:

Moodle Assignment #4 due at 8:00 AM Tuesday, May 4.

After studying this material you should be able to:

Distinguish between the concepts of macroevolution and microevolution.

Explain why evolution is considered both a fact and a scientific theory.

Discuss the limitations of the biological species concept, and explain why a species definition is important when investigating the concept of macroevolution.

Describe the importance of geographic isolation in the formation of a species.

Use the analogy of islands and barriers to describe the concept of geographic isolation and its role in speciation.

Provide examples of the different ways reproductive isolation can occur.

Explain the defining role of reproductive isolation in the formation of a new species.

Distinguish among allopatric, parapatric, and sympatric speciation.

Explain how speciation can occur within the same geographic region as the parental population (without geographic isolation).

interpret a phylogeny illustrating the relationships of a groiup of organisms.

Define these terms and describe the relationships among them:

Web Resources:

These links would provide good sources for Extra Credit Projects (due in Moodle 8:00 AM Thursday, April 29) or Moodle Assignment #4 (due 8:00 AM, Tuesday, May 4).

Evolution of human chromosome #2 by the fusion of two ape chromosomes from wikipedia.org

There are lots of great resources linked to this "library".

Don't believe the "intelligent design" proponents when they tell you the human eye is too complex to have evolved from a simpler structure.

Evolutionary Biology from the Talk.Origins archive.

Dealing with Antievolutionism, the importance of keeping the study of evolution in school curricula.

Before you take a stand, be sure you really understand your religion's view of evolution.

Pope John Paul II, Truth Cannot Contradict Truth Address to the Pontifical Academy of Sciences October 22, 1996

What is Macroevolution?

The process by which new species are produced from earlier species (speciation). It also involves processes leading to the extinction of species.

Occurs at the level of the species or above.

Such changes often span long periods of time (but can also happen rapidly).

Examples of macroevolution include: the origin of eukaryotic life forms the origin of humans the origin of eukaryotic cells and extinction of the dinosaurs.

In contrast, microevolution, involves evolutionary change at the level of the population, and is defined by changes in allele frequency within the population over time. Such changes take place over relatively short time periods.

Accumulated gradual changes in two populations that preclude their interbreeding may lead to the formation of a new species.

Some Examples of Macroevolution:

Mice, men share 99 percent of genes from CNN.com. The article says "Scientists say mice, humans and many other mammals descended from a common ancestor about the size of a small rat from 75 to 125 million years ago. That creature lived alongside the dinosaur. While mice and humans certainly don't look much the same these days, their genetic blueprints are startlingly similar."

Evolution of human chromosome #2 by the fusion of two ape chromosomes from wikipedia.org

Evolution as a Fact AND a Theory

Evolution, the change in the genetic composition of a population over time or the development of new species and extinction of previously existing species is FACT.

Evolution has occurred it still is occurring it has been directly observed, documented, demonstrated, and described. Supporting evidence for it is overwhelming (and obtained from a wide range of scientific fields).

The mechanisms by which we think evolution occurs (e.g., natural selection, mutation, genetic drift) are SCIENTIFIC THEORIES that explain these observed changes in living organisms over time.

Several theories to explain evolution have been proposed and debated by evolutionry biologists. It is far from clear how evolution proceeds in every detail or in every case, but the Fact that evolution has occurred is not questioned by the majority of biologists.

Recall Lecture One, Science as a Way of Knowing the Natural World. Once a hypothesis has been supported by many experiments and/or observations it is considered by the community of scientists to be a theory. (Note that this is very different from the common use of the word, meaning an opinion or a guess.)

In summary, Darwin established the FACT of evolution, and proposed a THEORY, natural selection, to explain the mechanism of evolution.

Evolution is a Fact and a Theory gives a very good explanation of this distinction.

If you are interested in the relationship of science and religion concerning the topic of evolution I invite you to consult these sources for further discussions.

Before you take a stand, be sure you really understand your religion's view of evolution. Science Faith and Politics from the PBS Evolution Library

Pope John Paul II, Truth Cannot Contradict Truth -- Address to the Pontifical Academy of Sciences October 22, 1996. In this treatise, Pope John Paul II describes how the scientific theories explaining evolution do not contradict the beliefs of the Catholic Church. This is a challenging, but very interesting read.

What is a Species?

As with our earlier discussion of species diversity, the biological definition of species is important in the discussion of MACROEVOLUTION.

When we talk about the evolution of new species from pre-existing species we need some criterion to determine when we are seeing a new species

The Biological Species Concept is the definition Hoefnagels uses in your text.

Biological Species - "A population, or group of populations, whose members can interbreed and produce fertile offspring.

Some Limitations to the Biological Species Concept (others exist)

Restricted to sexually reproducing organisms, so it does not apply to single celled organisms that reproduce by simple cell division (mitosis).

Some species are incredibly variable different species can be virtually identical.

Does not fit many plant species because they freely form hybrids.

No clear application to the fossil record, since reproductive isolation does not show up in fossilized materials.

DNA sequence comparisons can be used to assess relatedness of organisms, and is useful in assigning organisms to species when no other information is available.

Our definitions of species can change as our ability to detect differences among types of organisms changes.

New Species and Reproductive Isolation

The key to understanding the formation of new species is understanding how a population becomes reproductively isolated from other populations of the same species. Think of this as the isolation of gene pools (all the genes and their alleles in a population).

Understanding speciation is based on understanding HOW two populations can become genetically different enough to become unable to reproduce with each other.

If populations are not reproductively isolated, gene flow between the populations maintains their genetic similarity and they maintain the ability to interbreed, so new species do not form.

Populations that are not reproductively isolated may change genetically over time--they evolve (microevolution) --but those changes are shared among the populations by gene flow so they remain as one species.

"Evolution's human and chimp twist". (from BBC News) Gene flow between early humans and chimpanzees?

The rest of this outline describes the various ways in which this gentic reproducive separation can happen.

Some documented examples of the evolution of new species

Genetic Changes that Lead to Reproductive Isolation of Populations

New species arise when genetic differences accumulate to the point when the two populations can no longer successfully mate and reproduce. (Remember: species can be defined as "A group of similar individuals that breed sexually in nature only among themselves [produce fertile offspring]. "

For new species to form, reproductive isolation is necessary. Genetic changes can lead to a variety of isolating mechanisms. Some of these differences are the result of single gene mutations.

Premating or Prezygotic (isolating mechanisms that prevent the union of gametes it occurs before or during fertilization)

Mechanical Isolation. Mating organs do not fit [or are adapted for different pollinators].

Ecological Isolation. The two populations require different micro-habitats in the same general area.

Seasonal and Temporal Isolation. Populations are reproductively active or fertile at different times of year or day.

Behaviorial (or Ethological) Isolation. Different preferences or behaviors affect mate selection.

Gametic Isolation. Mating may be attempted, but the gametes cannot combine.

Chromosomal Isolation. Gamete chromosomes from the two parents are not compatible, so fertilization can not occur even if gametes can fuse.

Postmating or Postzygotic (mechanisms that reduce the viability or fertility of hybrid offspring)

Hybrid Inviability. Gametes combine, but development cannot produce a viable embryo.

Hybrid Infertility. Offspring lack the ability to make or deliver viable gametes. (Horse X Donkey = Sterile Mule, due to different chromosome numbers of parents mitosis occurs normally, but meiosis is impossible)

Geographic Relationships in the Process of Speciation

In some instances, two populations are isolated in different geographic locations so that initial reproductive isolation of two populations is affected by geographic isolation.

Subsequent genetic changes resulting from the forces of natural selection, genetic drift, migration, nonrandom mating, and mutation in the two geographically isolated populations can, but don't necessarily, result in reproductive isolation and the evolution of new species.

In other examples, genetic changes can occur in two groups within the same or adjacent habitats and produce reproductive isolation and new species.

A common misconception is that formation of new species requires geographical isolation. Geographic isolation may be involved, but that is not always the case.

The important criterion is that there must be reproductiove isolation and that CAN occur without geographic isolation.

Allopatric Speciation

allo = other and patric has to do with country, as in patriot - a person who loves one's country. Allopratric speciation is literally speciation that occurs in different countries.

Members of two newly formed populations cannot interbreed because they are geographically separated.

Think of this as the concept of islands and barriers:

Islands of land in a sea of water

Islands of water in a sea of land

Islands of trees in a sea of grass

Islands of coolness in a sea of heat

Islands of warmth in a sea of cold

Islands of nature in a sea of humanity

Rivers and canyons as barriers

Stages in the formation of a new species (from Grant, 1963 and 1981, and the University of Alabama).

Illustrative example of Allopatric Speciation from the University of Alabama. This figure shows the separation of two populations by some geographic barrier over time. Subsequent divergence leads to the formation of different species. The species are reproductively isolated when that barrier is removed.

Darwin's finches from the University of Alabama.

If a population should become divided into two by a geographic barrier (or if some individuals are transported to a new area outside the parent population's range), evolution of each new population continues independently due to the forces of natural selection, genetic drift, migration, nonrandom mating, and mutation. With time, genetic differences between the two populations gradually accumulate. These genetic differences may result in different reproductive requirements, leading to the reproductive isolation of the populations.

Microevolution becomes macroevolution once a population divides and sufficient genetic divergence between the groups occurs so that if they once again come in contact, they could no longer produce fertile offspring (i.e., they are different, yet closely related species).

Allopatric speciation: The formation of new species when two populations are physically separated by a geographic barrier, such as this illustration of white and brown tamarin monkey populations on different sides of the Amazon River (Text figure 14.5, pg 292).

Parapatric Speciation

The formation of a new species when populations inhabit neighboring areas but mate mostly among themselves, such as seen in these tropical little greenbul birds (Hoefnagels, figure 15.6, pg 293).

Sympatric Speciation

Geographic isolation is NOT always necessary for speciation to occur.

Genetic changes can occur in some individuals in a population that result in their reproductive isolation from the rest of the population.

Speciation can occur within the range of the parent population (and sometimes quite rapidly).

Gene flow may be disrupted by several types of genetic change:

Genetic changes that affect the form of the reproductive structures in some individuals.

Genetic changes that affect the physical characteristics that are important in mate selection in some individuals.

Genetic changes that affect behaviors that are important in mate selection in some individuals.

Genetic changes that affect the time of reproduction in some individuals.

Genetic changes that affect the ability of gametes to fuse in some individuals.

Genetic changes that affect the chromosome numbers or compatibility in some individuals.

Polyploidy - individuals have multiple SETS of chromosomes that prevent sexual reproduction.

autopolyploid - extra chromosome sets occur from matings within the from the SAME species. Mistakes in meiosis or mitosis produce zygotes with multiple sets of chromosomes.

allopolyploid - extra chromosome sets occur from matings of DIFFERENT species through hybridization)

These polyploids can self-fertilize or breed among themselves.

In humans and other animals, polyploidy is lethal. In plants, polyploidy is quite common. It has given rise to many new species. It is estimated that as many as 50% of extant flowering plant species have evolved via hybridization and polyploidy.

Choice of host plant or habitat (the utilization of different resources)

The natural host of the American fruit fly is a hawthorn tree however, some flies live in apple trees. By eating, courting, mating, and laying their eggs on different host plants, the two groups of flies have become reproductively isolated from one another and are on their way to becoming different species. Genetic differences between these groups can be measured.

In many organisms, shifts to new host plants or habitats trigger phenotypic changes that lead to new species.

An Example of Speciation by Hybridization and Polyploidy Tragopogon

Three species of salsify (vegetable oyster) were introduced from Europe.

T. dubius, T. porrifolius, and T. pratensis

All three species occur in SE Washington and adjacent Idaho, in an area known as the Palouse.

Only T. dubius and T. pratensis occur in Illinois and they are not that common, mostly road-side weeds.

When two or more species co-occur, natural hybrids are found.

However, these hybrids are sterile.

In 1949, fertile individuals were discovered! These are new species, because they can not hybridize with any of the original three species. They have twice the number of chromosomes as the original three species. The relationships among these species can be seen in the "Tragopogon Triangle"

Speciation and Time

An evolutionary tree (or phylogeny), depicting rates and times of speciation and extinction events. Evolution occurs in a branching pattern, with one species giving rise to others as they occupy and adapt to new habitats. They descend from an original ancestral form, much as the branches on a tree arise from the same trunk. (Text figure 17.9, pg. 311)

A phylogeny depicts species' relationships based on descent from shared ancestors.

Adaptive Radiation: the divergence of several new types of organisms from a single ancestral type. When a population faces an environment with abundant and diverse resources (such as the opening up of many new habitats), a burst of speciation can occur if members of a population inherit a structure or ability that gives them an advantage.

Adaptive radiation of mammals, after extinction of the dinosaurs (Previous text fig).

The finches and tortoises of the Galapagos Islands.

Speciation events lead to the multiplication and diversification of species into higher taxa (e.g., genera, families, orders, classes, phyla, etc.). All species (animals, plants, fungi, and all major groups of microorganisms) can be traced back to a single origin of life on earth. Evolution is a continuing process that explains the history of life on earth, as well as the diversity of life today.

Species Extinctions

Extinction: the disappearance of a species, or the inability of a species to adapt to a particular environmental challenge.

Decreased genetic diversity may lead to extinction of populations and, eventually, the species.

The history of the earth is punctuated by several mass extinctions (see (previous text table 17.1, pg. 316)). Mass extinctions have periodically opened up vast new areas for adaptive radiation to occur. See Hoefnagels, pg 298-9.

As mentioned in the biodiversity lectures, the number of organisms on Earth is now being reduced at a rate 1,000-10,000 times higher than any time prior to the evolution of humans (that is, a few decades or centuries rather than millions of years)


Linking local species interactions to rates of speciation in communities.

Explaining patterns of species diversity is an enduring problem for community ecologists. Since Hutchinson (1958, 1959) questions concerning species diversity have been directed primarily at understanding the processes that regulate the number of coexisting species. In studying these processes, community ecologists generally assume a paradigm in which a defined pool of species exists, and each member of the pool can potentially colonize every site under consideration (e.g., as exemplified by the elegant laboratory experiments of Neill 1975, Robinson and Dickerson 1987, Drake 1991, Lawlor and Morin 1993). Once the potential pool of species is defined, ecological studies are directed at examining why only a subset of species in the pool can coexist in any particular ecological setting, and why different numbers of species coexist in different settings (e.g., marine intertidal: Connell 1961, Paine 1966, 1969, 1974, 1980, Lubchenco 1978, 1980 freshwater lakes: Brooks and Dodson 1965, Hall et al. 1970, Dodson 1970, 1974, Sprules 1972, Addicott 1974, Post and Cucin 1984, Vanni 1986, 1988, McPeek 1990 freshwater streams: Griffiths 1981, Flecker 1992 terrestrial plants: Harper 1969, Whittaker 1975, Tilman 1982, 1988).

This paradigmatic approach is appropriate for examining the processes that promote or retard species coexistence once the pool is defined, but it begs the question of how the species pool was created in the first place. The pool of potential species in a given biogeographic area is increased by speciation of existing taxa or by dispersal into the area by new taxa species are lost from the pool by extinction or by migration out of the area (Rosenzweig 1975, Platnick and Nelson 1978, Stanley 1979, Humphries and Parenti 1986, Eldredge 1989). Community ecologists are beginning to recognize that local diversity patterns are greatly influenced by regional processes such as speciation, extinction, and biogeographic history (Ricklefs 1987, 1989, Brown and Nicoletto 1991, Cornell and Lawton 1992, Cadle and Green 1993, Ricklefs and Schluter 1993). The importance of macroevolutionary and biogeographic processes are most clearly apparent in systems where local species interactions have little or no influence on local diversity (e.g., Strong et al. 1984, Cornell 1985a, b, 1993, Cornell and Lawton 1992), but macroevolution and biogeography can similarly influence species diversity in communities where strong species interactions regulate coexistence. For example, in a particular ecological setting many interacting species may be capable of coexisting, but few may exist there at any one time, because either low speciation rates, high extinction rates, or lack of dispersal constrain species richness. Consequently, interpreting diversity patterns from a purely ecological perspective is flawed.

Extinction is already an integral part of the conceptual framework of community ecology, since population extinction is a predictable and understandable outcome of species interactions on a local scale (e.g., competitive exclusion) that is easily generalizable to regional scales. Additionally, much of the present effort in conserving biological diversity is directed at understanding the processes that lead to extinction (e.g., Boecklin and Simberloff 1985, Soule 1987, Lawton and May 1995), because of extinction's immediate and irreparable impacts.

In contrast, the links between species interactions and speciation are rarely considered. Many speciation mechanisms may operate largely autonomously of the ecological setting, e.g., vicariance (Cracraft 1982, 1985), hybridization and polyploidy (Grant 1981), mating system evolution (Barrett 1989). When these modes of speciation predominate, new species will be introduced "at random" into local communities via speciation and dispersal from other biogeographic areas, and extinctions caused by local interactions will be the primary ecological contributor to regulating local diversity (MacArthur and Wilson 1967, Rummell and Roughgarden 1985).

Shifts in habitat occupancy or host use by lineages commonly create new species (Rice 1985, 1987, Feder and Bush 1991, Tauber and Tauber 1989, Futuyma and McCafferty 1990, McPeek 1995a, b). These habitat or host shifts are thought to create new species when a founder population of a species adapted to one community type is established and subsequently adapts to a new community type. Species interactions can influence the potential for successful habitat shifts by affecting the likelihood that founder populations will adapt to their new ecological milieu before becoming extinct (Gomulkiewicz and Holt 1995). Key innovations to the new ecological environments may heighten speciation rates in lineages following habitat shifts (Simpson 1953, Mitter et al. 1988, Farrell et al. 1991), but the conditions that cause certain phenotypes in novel environments to be key innovations are unknown and may be unpredictable (Mitter et al. 1988, Farrell et al. 1991, Allmon 1992).

Ecologists have long postulated that species interactions, especially competition leading to character displacement, can generate diversification of a taxon into multiple niches within the same local community (e.g., Pimm 1978, Rosenzweig 1978, Wilson and Turelli 1986, Wilson 1989). Although mechanisms such as character displacement have contributed to the evolutionary divergence of already existing species to promote their coexistence in areas of sympatry, clear examples demonstrating that these mechanisms have caused speciation sympatrically in one lineage are however rare (see recent reviews by Schluter and MacPhail 1993, Robinson and Wilson 1994).

Evolutionary biologists generally acknowledge that allopatric speciation via divergent selection in different regions of a species range is one of the most common and potentially most powerful mechanisms for generating new species, especially in animals (Mayr 1942, 1963, Lynch 1989, Allmon 1992, Rice and Hostert 1993, Coyne 1994). Rice and Hostert (1993) reviewed laboratory experiments that simulate the major mechanisms of speciation and concluded that the allopatric model of speciation in which "multifarious, strong, discontinuous, divergent" selection in different parts of a species' range can relatively rapidly generate reproductive isolation even with gene flow. Consequently, any mechanism that can influence the disparity in natural selection experienced by populations across the range of a species will regulate to a substantial degree the potential for speciation in that species.

Although the importance of allopatric speciation has long been recognized, community ecologists have been surprisingly silent about how ecological interactions in general and species interactions in particular could influence the potential for allopatric speciation. Since species interactions are major ecological forces determining the form of natural selection experienced by most organisms (Endler 1986), variation in the types and strengths of interactions across a species' range may critically determine its potential for undergoing speciation. Moreover, speciation rates for many taxa in a given environment could be strongly influenced by the scope of large-scale geographic variation in species interactions.

In this paper I describe one way in which species interactions operating in local communities may influence the potential for speciation by influencing the potential for generating differentiation across the range of a species as hypothesized in the allopatric speciation model with regional differences in selection. The relative strengths of selection experienced by a population can have profound effects on the shape of the overall fitness surface. Using a simple model of fitness I show that even when the same trait values are favored by various agents of natural selection, the relative strengths of selection imposed by various selective agents will modulate the degree of population differentiation that can be generated by natural selection, and thus the potential for allopatric speciation via response to local selection pressures that vary across the range of a species. This analysis indicates that the relative strengths of selection imparted by various niche axes can be as important to diversification as the number of niche axes along which populations can differentiate. Because the strength of ecological interactions can also influence the number of coexisting species, and if the strength of an interaction is positively related to the strength of selection imposed by that interaction, this mechanism suggests a possible link between the ecological processes regulating local species diversity and the macroevolutionary processes generating new species.

Local Interactions and Population Differentiation

Can local interactions influence regional processes which affect the potential for population differentiation and thus allopatric speciation? A number of authors have argued that the primary force preventing population differentiation that would lead to allopatric speciation is the similarity in selection pressures experienced by different populations across the range of a species (e.g., Ehrlich and Raven 1969, Lande 1980). Conversely, if populations in different parts of a species' range experience different selection regimes, populations in these different areas may evolve to the point of differentiation that can lead to speciation (Ehrlich and Raven 1969, Endler 1977). The results of laboratory experiments indicate that such differences in selection pressures across a species' range could rapidly generate reproductive isolation via pleiotropic or genetic hitchhiking effects, even with substantial gene flow (reviewed by Rice and Hostert 1993). In this section I outline how the relative strengths of local selective agents can influence the potential for population differentiation across the range of a species by influencing the shape of the fitness surfaces experienced by different populations.

Local ecological interactions will influence the potential for speciation by generating variation in the shapes of fitness surfaces experienced by populations across the range of a species. The distribution of a species is a mosaic of local populations embedded in local communities. For example, for a species inhabiting lakes, each lake supports a separate population, and the species range is the geographic area encompassing the collection of lakes inhabited by the species. The fitnesses of individuals in a particular population are influenced by the local abiotic environment and interactions with resources, competitors, predators, diseases, etc., in the local community. Each ecological interaction, which is also potentially an agent of natural selection, may generate a unique relationship between some component of fitness (survival or fecundity schedules) and the phenotype (i.e., fitness components of Arnold and Wade 1984). The overall fitness surface experienced by a population is then a function of all the component interactions that contribute to determining overall fitness (Lande 1979, 1980, Arnold and Wade 1984).

Some ecological interactions may be regular features of all local communities inhabited by a species and in fact may define species composition of the community (e.g., keystone species sensu Paine [1966, 1980]), whereas other types of interactions may vary in importance across a species' range. Each population will be evolving according to the fitness surface generated by local ecological conditions. Although current theoretical development of how multiple selective agents may influence selection dynamics is sparce, I use a simple model of fitness surfaces to illustrate how variation in the strengths of selection from various selective agents acting in local populations can profoundly influence the degree of differences between fitness surfaces experienced by populations and thus the potential for population differentiation and speciation.

For simplicity I will consider the case in which only two selective agents act on one phenotypic character in any one population. One phenotypic character may often simultaneously experience selection from multiple selective agents. For example, in many prey species activity level will influence both survival under predation and feeding rates, which should both be strong determinants of fitness (e.g., Sih 1980, 1982, Kohler and McPeek 1989, Werner and Anholt 1993, Werner and McPeek 1994). Growth rate can also be simultaneously under selection generated by both predation and competition (e.g., Wilbur 1984, Travis et al. 1985). Germination date in plants may experience selection via competitive interactions and abiotic factors such as the timing of frosts (Kalisz 1986, Miller 1987, van der Toorn and Pons 1988, Biere 1991, Stratton 1992). Arnold and Wade (1984) have examined how total lifetime fitness is decomposable into separate fitness components. When fitness components are multiplicative, the fitness component generating the largest strength of selection will have the greatest effect on the overall fitness function (Arnold and Wade 1984). This result is important for understanding changes in the fitness surfaces experienced by populations as selective agents vary across the range of a species.

To illustrate how differences in the type and strength of different selective agents acting on one character can influence the potential for population differentiation, consider the following scenario. A species occupies one community type and has two areas to its range [ILLUSTRATION FOR FIGURE 1a OMITTED] these areas may be different geographic regions or the main body of the range and some peripheral populations. In the first area, two selective agents act on one character to determine overall fitness [ILLUSTRATION FOR FIGURE 1a OMITTED]. Each selective agent imposes optimizing selection, and both impose similar strengths of selection, but the optimal phenotypic value differs for the two agents (Fitness Components in [ILLUSTRATION FOR FIGURE 1a OMITTED]. With optimizing selection the strength of selection characterizes the change in fitness as the phenotype is changed away from the optimum (Lande 1979). (The curves for the two fitness components pictured in Fig. 1a are both Gaussian in form, where the formula for each is Fitness Component = exp[-[(z - [Mu]).sup.2]/2[Omega]]: z is the phenotypic value [Mu] is the optimal phenotype [Omega] is the parameter that defines the width of the curve and quantifies the strength of selection. [Omega] = 20 for both of these fitness components. All of the results pictured in Fig. 1 and discussed in the text are easily derived analytically.) Overall fitness, which is a multiplicative function of the two fitness components (Lande 1979, Arnold and Wade 1984), is maximized at a phenotypic value that is exactly intermediate in this case to the two separate fitness component optima (Fitness in [ILLUSTRATION FOR FIGURE 1a OMITTED]. (Note that this intermediate optimum is the evolutionary characterization of what community ecologists discuss as trade-offs [cf. Lubchenco 1978, Schoener 1986, Tilman 1987].) In contrast, in the other area of the range one of the selective agents found in the first area is also present (this may be a keystone interaction that defines the community's species composition), but the other selective agent is replaced by a new selective agent that favors another trait value [ILLUSTRATION FOR FIGURE 1a OMITTED]. Again, the strength of selection for both selective agents is the same (again [Omega] = 20). Overall fitness in this area is maximized at a trait value that is substantially different from that of the first area [ILLUSTRATION FOR FIGURE 1a OMITTED]. Differences in selection regimes between these two areas should promote population differentiation, because different trait values are favored in the two areas of the species range. This difference in selection regimes between the two regions of the species range should therefore be conducive to generating allopatric speciation (Rice and Hostert 1993).

Now consider another species that exists in another community type [ILLUSTRATION FOR FIGURE 1b OMITTED]. This species has similar differences in selective agents among populations, but the selective agents also differ in the strength of selection they impose. One agent imposes strong selection on the trait and is common to both areas (the ubiquitous fitness component pictured in [ILLUSTRATION FOR FIGURE 1b OMITTED] has [Omega] = 1: note that the strength of selection increases as to decreases), while other selective agents are unique to each area and impose much weaker selection ([Omega] = 20 for these selective agents in [ILLUSTRATION FOR FIGURE 1b OMITTED]). The optima for the fitness components are at the same trait values as in the previous example only the strengths of selection differ [ILLUSTRATION FOR FIGURE 1b OMITTED]. Again in each area, the optimal trait value in overall fitness is intermediate to the separate fitness component optima, but now the overall optimum is very near the optimum for the component with strong selection. Consequently, the optima for the two areas are very near to one another, and the fitness curves for the two areas largely overlap [ILLUSTRATION FOR FIGURE 1b OMITTED]. Little or no population differentiation will occur between the two areas even though the agents of selection are quite different in the two areas, the adaptive topographies are almost identical because their shapes are predominantly defined by the strong selective agent that is common to both areas. Consequently, little potential exists for speciation via allopatric differences in selection in this environment.

The results of simulations (M. A. McPeek, unpublished data) indicate that similar outcomes of population differentiation can be achieved when separate selective pressures act independently on two phenotypic characters that are genetically correlated because of shared pleiotropic loci and the genetic correlation is also allowed to evolve.

Natural selection may constrain or enhance the potential for population differentiation that can lead to allopatric speciation. It has been argued that natural selection is the primary evolutionary force determining whether populations of a species remain a cohesive unit or are disrupted onto separate evolutionary trajectories (Ehrlich and Raven 1969, Lande 1980). If populations experience similar selective surfaces, cohesion is likely since the same relationship between fitness and phenotype will exist in all populations. Populations may explore the adaptive surface by undergoing shifts between adaptive peaks, but any resulting new adaptation can be dispersed throughout the species range to generate peak shifts in the rest of the populations (Wright 1932, Lande 1980, Crow et al. 1990, Phillips 1994). Population differentiation should be much more likely when populations experience different selective surfaces (Ehrlich and Raven 1969, Endler 1977). In this case, selection is a consistent evolutionary force generating different adapted phenotypes among populations. This is true even with significant gene flow (Endler 1977, Rice and Hostert 1993). However, selection on dispersal propensity generated by spatial variation in fitness should also favor a reduction in gene flow between areas with different selection surfaces (Gadgil 1971, Balkau and Feldman 1973, Hastings 1983, Holt 1985, McPeek and Holt 1992), which will further promote differentiation. Therefore, any mechanism that causes populations of a species to experience different selection surfaces should have a tremendous impact on the potential for speciation (Endler 1977, Rice and Hostert 1993).

Studies of community organization suggest that some selection pressures will be consistent environmental features of a community type and others may vary from locality to locality. Two of the best studied systems are the rocky intertidal and freshwater lakes. Paine (1980) in his review of rocky intertidal community structure shows that Pisaster seastars are a consistent organizing force influencing species richness all along the western North American coast, but the composition and importance of other species as well as abiotic factors change with latitude. In freshwater lakes characteristic zooplankton communities develop in the presence and absence of fish (Hrbacek et al. 1961, Brooks and Dodson 1965, Hall et al. 1970, Zaret 1980, Vanni 1986, 1988): small-bodied species with fish, and large-bodied species in fishless lakes. In these communities, fish predation defines species composition and contributes to the regulation of coexisting species, but other ecological features, such as productivity (Carpenter et al. 1985, McQueen et al. 1986, 1989), algal and zooplankton abundances (Stemberger and Lazorchak 1994), and structural complexity (Tessier and Weiser 1991), can vary greatly among lakes. Some ecological interactions, such as Pisaster predation in the intertidal or fish predation in fish lakes, strongly influence species composition and thereby define the community type these "keystone" interactions (Paine 1966, 1974) and their associated selection pressures will be ubiquitous selective agents acting on all populations of a species in a given community type. Other interactions, which are not primary determinants of species composition but rather primarily influence the abundances of species within the community, and their associated selection pressures can vary in importance among local populations.

The relative strengths of selection imposed by ubiquitous interactions and interactions that vary substantially among populations will influence the degree to which population differentiation can develop within a species [ILLUSTRATION FOR FIGURE 1 OMITTED]. If the ubiquitous and local selection pressures are relatively similar in strength, local populations will be able to adapt along niche dimensions that vary among populations this will promote population differentiation and therefore allopatric speciation. If, however, the ubiquitous selective agents impose much stronger selection than local selective agents, populations will be constrained from adapting to local conditions that vary among populations, and the potential for speciation will be retarded. The potential for speciation is enhanced as selection strengths become more similar because greater variation in the overall fitness surfaces experienced by different populations can be achieved [ILLUSTRATION FOR FIGURE 1 OMITTED].

Selective agents that vary among local populations need not only be environmental factors, but could also be sexual selection pressures. Natural and sexual selection are generally thought to act on the same traits or correlated sets of traits (Fisher 1958, Lande 1981, Thornhill and Alcock 1983, Kodric-Brown and Brown 1984, Lande and Kirkpatrick 1988). Weaker natural selection may allow sexual selection to generate greater differences in mating preferences among local populations which could lead to speciation (West-Eberhard 1983). Alternatively, sexual selection may reinforce niche differentiation, permitted by weaker selection from ubiquitous selective agents, to enhance synergistically the potential for speciation (Lande and Kirkpatrick 1988). Speciation due to differentiation of mate choice or sexual recognition may therefore not be independent of changes in the strength of natural selection within communities.

These considerations generate a number of testable predictions about how ecological and evolutionary processes interact to influence species diversity in communities structured by species interactions. (1) Species in less diverse communities should display less population differentiation across their ranges in ecologically important phenotypic characters, because less local adaptation should be possible. This is because (2) greater disparities should exist among the strengths of selection imposed by various selective agents in less diverse communities, and consequentially (3) the shapes of fitness surfaces should vary less among populations for species in less diverse communities [ILLUSTRATION FOR FIGURE 1 OMITTED]. (4) Speciation rates in component taxa should be higher in more diverse communities. It is somewhat disheartening to realize that almost no data are available to evaluate these predictions. Testing these predictions will require combining ecological and evolutionary methodologies to study community structure, and therefore should foster cross-discipline exchanges and collaborations. Measuring the strengths of species interactions and the resulting selection can be combined in the same experimental manipulations of competitors, resources, predators, etc. (e.g., Miller et al. 1994). Observational and experimental studies quantifying the fitness surfaces in multiple populations will be invaluable for interpreting the causes of population differentiation (Wade and Kalisz 1990). Finally, phylogenetic studies of component taxa can not only provide estimates of diversification rates for comparison among communities (e.g., Mitter et al. 1988, Farrell et al. 1991), but also for reconstructing the history of community structure development over time (Futuyma and McCafferty 1990, McPeek 1995a, b).

The number of local niche dimensions is often cited as influencing the potential for diversification within communities (Begon et al. 1990, Ricklefs 1990, Krebs 1994). This analysis shows that the relative strengths of selection imposed by various selective agents (i.e., along various niche dimensions) can have as much or more to do with the potential for diversification as the number of axes along which diversification can occur. In the example discussed above [ILLUSTRATION FOR FIGURE 1 OMITTED], the number of "niche axes" available for populations to diversify along was always the same. The potential for differentiation among populations is governed by the relative strengths of selection imposed by the various ecological interactions defining the niche axes. Differentation of taxa could be greater in a community type with relatively few local niche dimensions, weak interactions and weak selection pressures than in a community type with many local niche dimensions but one strong interaction and consequently one strong selection pressure.

Coexistence and speciation. - Do the ecological conditions that promote the coexistence of many species also foster high speciation and/or low extinction rates? We must begin to address such questions theoretically and empirically if we are to understand fully patterns of species diversity. For the mechanism I discuss in this paper, a loose congruency could potentially exist between the number of coexisting species and the potential for generating new species in a community. The strength of selection generated by an ecological interaction should be related to the magnitude of effects the interaction has on overall birth and death rates, i.e., the "strength" of the ecological interaction (Paine 1980). For example, in a study of 16 populations over 4 yr, Weis et el. (1992) found that the strength of selection on the gall-making insect Eurosta solidaginins was positively correlated with the mortality imposed by parasitoid wasps. Mechanisms of competition should operate in an analogous fashion as competitor abundances increase, resource levels will decrease, which will place a premium on having competitively superior phenotypes. The strength of selection on emergence date in plants has been shown to increase as conspecific density (Miller et al. 1994) and heterospecific density (van der Toorn and Pons 1988, Stratton 1992) increases, presumably as a result of increases in the strength of competition.

A common pattern observed in nature is that the number of coexisting species decreases as the strength of interactions among species increases (Paine 1966, 1969, 1974, 1980, 1988, Harper 1969, Addicott 1974, Lubchenco 1978, Duggins and Dethier 1985, Turner 1985, Gibson 1988), and ecological theories that encapsulate various mechanisms of interactions among species can generate this relationship (e.g., May 1973, Holt 1977). For example under the keystone predator hypothesis (Paine 1966, 1969, 1974), species diversity should be low in areas where the keystone predator is absent, because the strength of competition with the dominant competitor should be greatest in the absence of the predator and thus drive all other species extinct via competitive exclusion. Diversity should also be low when the keystone predator is very abundant the strength of predation under this condition drives most prey species locally extinct. Diversity is predicted to be highest at intermediate predator densities where the strengths of competition and predation are both much weaker than their potential maxima. General food web theory also predicts that the number of coexisting species should decrease as the average strength of species interactions in a community increases (May 1973). The frequency and intensity of disturbance can also generate such diversity patterns (e.g., Connell 1978, Huston 1979).

Consequently, in a community in which a strong ecological interaction dominates, few species are expected to coexist and if this dominant interaction imposes much stronger selection than other interactions, the potential for allopatric speciation in component taxa should be impeded [ILLUSTRATION FOR FIGURE 1B OMITTED]. Conversely, if the populations of component taxa in a community are regulated by relatively weak interactions and interactions impose relatively similar strengths of selection, many species may be able to coexist, and the potential for allopatric speciation in component taxa may be enhanced. Obviously, not all strong selection pressures will necessarily result from strong ecological interactions, just as not all strong ecological interactions will necessarily generate strong selection on the phenotype. However, abundant evidence indicates that ecological interactions generate natural selection (see Endler 1986 for a general review) and that the strength of selection can covary with the strengths of interactions (reviewed by Travis 1990).

At present, the data needed to evaluate whether the strengths of ecological interactions and the strengths of selection are positively correlated across communities, and whether these processes interact to influence species diversity, do not exist. Ideally, one would correlate (1) the changes in birth or survival rates associated with manipulations of major predators or competitors in field experiments with (2) the strengths of selection gradients on phenotypic characters determining performance in these ecological interactions in natural populations in communities that vary in species diversity. Studies of interaction strengths and selection strengths are commonly being conducted separately to many systems (field experiments of species interactions: see reviews by Connell 1983, Schoener 1983, Sih et el. 1985, Hairston 1989, Goldberg and Barton 1992 quantifying natural selection in the field, e.g., Kalisz 1986, Brodie 1992, King 1994), but few studies simultaneously evaluate the strength of an ecological interaction and natural selection imposed by that interaction (see above references). Therefore, relating any covariance among them to diversity patterns is presently impossible. Also, more explicit theory linking mechanisms of various types of ecological interactions to the phenotypes of component species and thereby to the mechanisms generating the shapes of individual fitness surfaces is sorely needed.

Other mechanisms linking ecology and speciation. - Obviously, the process I have described is only one of many by which ecological interactions could influence speciation rates. The mechanisms described above will be most applicable in environments where species interactions strongly influence species composition in local communities and temporal variation in local environmental conditions is relatively small (e.g., marine intertidal, and freshwater lentic and lotic communities). My goal in this paper is not to develop a complete framework for these linkages under all possible conditions, but rather to stimulate thought on the general topic and explore the problem in one set of environmental conditions. I briefly mention two others.

"Key innovations" are often invoked as a reason why some communities have more species than others. "Key innovations" are phenotypes that are associated with higher diversification rates in certain lineages (Bock 1985). The mechanisms presented above may also be relevant to why key innovations may lead to higher speciation rates. Implicit in discussions of key innovations is the idea that possessing a new phenotypic trait alters selection pressures on the entire phenotype (Simpson 1953, Stanley 1979, Benton 1988, Eldredge 1989), but how changing the selection regime alters the potential for speciation remains unclear (Mitter et al. 1988, Allmon 1992). In lineages that do not possess the key innovation, strong selection pressures on one set of characters may prevent adaptation along other niche axes or to sexual selection pressures that could lead to population differentiation (i.e., [ILLUSTRATION FOR FIGURE 1B OMITTED]). However, if the new phenotypic trait relaxes selection from a strong selective agent, populations may be better able to respond to other selection pressures that may promote differentiation [ILLUSTRATION FOR FIGURE 1A OMITTED]. In this case the important feature to relaxing selection is a difference in the phenotype rather than a difference in the external environment key innovations may be associated with habitat shifts, but it is possession of the new phenotype that is thought to promote higher speciation rates. Farrell et al. (1991) have shown that plant lineages possessing latex and resin canals have higher diversification rates than sister groups lacking canals. They concluded that the relaxation of selection due to herbivores was probably the cause of higher diversification rates. Other hypotheses exist for why key innovations may lead to greater diversification (Mitter et al. 1988, Allmon 1992, Brooks and McLennan 1993). However, if the relaxation of one selection pressure promotes diversification via responses to others, not only should speciation rates increase in lineages possessing the key innovation, but also these lineages should cover a much wider range of phenotype space than sister clades without the key innovation.

The degree of temporal variation in environmental conditions may also substantially influence speciation rates in communities (Sanders 1968, Slobodkin and Sanders 1969, Jackson 1974, Jablonski 1986). Temporal variation will influence the evolution of both adaptations to local environmental conditions and dispersal rates between populations (Levins 1964, Holt 1987, McPeek and Holt 1992). In this paper, I have considered only the case where interactions and the resulting fitness surfaces in local populations do not vary substantially through time. Under these conditions, greater spatial variation in environmental conditions will promote greater levels of differentiation, if ubiquitous selection pressures for the community type are not relatively strong. Spatial but no temporal variation will concomitantly select for decreased dispersal among populations (Gadgil 1971, Balkau and Feldman 1973, Hastings 1983, Holt 1985, McPeek and Holt 1992), which will reduce gene flow. Consequently, both local adaptation and the evolution of dispersal should promote population differentiation under these conditions.

In contrast, temporal variability in ecological conditions will favor strategies that can survive over the range of conditions experienced in local populations: either individuals with phenotypes that are a compromise of those most favored under each separate set of conditions experienced (i.e., a "jack-of-all-trades": Levins 1968, MacArthur 1972, Felsenstein 1979) or individuals that are phenotypically plastic (Levins 1968, Smith-Gill 1983, Via and Lande 1985, Sultan 1987, Moran 1992). Spatial and temporal variability also favor high dispersal rates and therefore potentially high gene flow rates among populations (Gadgil 1971, Kuno 1981, McPeek and Holt 1992). With spatial and temporal variation both adaptation to local conditions and the evolution of dispersal should retard population differentiation. The potential for speciation via population differentiation should therefore decrease as the degree of temporal variability in local conditions increases (Slobodkin and Sanders 1969, Jablonski 1986).

The mechanisms generating and maintaining species diversity may be as numerous as the types of environments that exist in nature, and there is no reason to believe that only one mode of speciation will operate in one system. Species diversity may be regulated to varying degrees by species interactions in different systems (e.g., terrestrial insect communities vs. invertebrates in freshwater lakes). Speciation and extinction rates may also be influenced to varying degrees by ecological processes in different systems in some systems speciation may proceed predominantly by polyploidy, vicariance events, or drift, while ecological processes such as the strength of selection or variability in environmental conditions may have primacy in others. Processes governing coexistence and processes governing diversification may also be integrated to varying degrees in different systems. Moreover, multiple mechanisms may simultaneously operate to create new species in systems. Our goal should not be to derive one general model to cover all situations. Rather, models encapsulating properties associated with different systems are required. Generality will emerge when we understand which properties cause different mechanisms to operate in different systems. Development of such a theory will build strong mechanistic links between community ecology and macroevolution.

Electronic discussions with Alice Winn and old-fashioned conversations with Jonathan Brown, Mark Kirkpatrick, Joe Travis, and Earl Werner helped focus my thinking on this topic. Comments by two anonymous reviewers greatly aided in clarifying the presentation. Gail and Curtis McPeek inspired me throughout the development and writing of this paper. This work was supported by NSF grants DEB-9307033 and DEB-9419318.

Addicott, J. F. 1974. Predation and prey community structure: an experimental study of the effect of mosquito larvae on the protozoan communities of pitcher plants. Ecology 55:475-492.

Allmon, W. D. 1992. A causal analysis of stages in allopatric speciation. Oxford Surveys in Evolutionary Biology 8:219-258.

Arnold, S. J., and M. J. Wade. 1984. On the measurement of natural and sexual selection: theory. Evolution 38:709-719.

Balkau, B. J., and M. W. Feldman. 1973. Selection for migration modification. Genetics 74:171-174.

Barrett, S. 1989. Mating system evolution and speciation in heterostylous plants. Pages 257-283 in D. Otte and J. A. Endler, editors. Speciation and its consequences. Sinauer, Sunderland, Massachusetts, USA.

Begon, M., J. L. Harper, and C. R. Townsend. 1990. Ecology: individuals, populations and communities. Second edition. Blackwell Scientific, Boston, Massachusetts, USA.

Benton, M. J. 1988. The nature of an adaptive radiation. Trends in Ecology and Evolution 3:127-128.

Biere, A. 1991. Parental effects in Lychnis flos-cuculi. II. Selection on time of emergence and seedling performance in the field. Journal of Evolutionary Biology 3:467-486.

Bock, W. J. 1985. Adaptive inference and museological research. Occasional Papers of the British Columbia Provincial Museum 25:123-138.

Boecklin, W. J., and D. Simberloff. 1985. Area-based extinction models in conservation. Pages 247-276 in D. K. Elliott, editor. Dynamics of extinction. John Wiley & Sons, New York, New York, USA.

Brodie, E. D., III. 1992. Correlational selection for color pattern and antipredator behavior in the garter snake Thamnophis ordinoides. Evolution 46:1284-1298.

Brooks, J. L., and S. I. Dodson. 1965. Predation, body size, and composition of plankton. Science 150:28-35.

Brooks, J. L., and D. A. McLennan. 1993. Comparative study of adaptive radiations with an example using parasitic flatworms (Platyhelminthes: Cercomeria). American Naturalist 142:755-778.

Brown, J. H., and P. F. Nicoletto. 1991. Spatial scaling of species composition: body masses of North American land mammals. American Naturalist 138:1478-1512.

Cadle, J. E., and H. W. Green. 1993. Phylogenetic patterns, biogeography, and the ecological structure of Neotropical snake assemblages. Pages 281-293 in R. E. Ricklefs and D. Schluter, editors. Species diversity in ecological communities: historical and geographical perspectives. University of Chicago Press, Chicago, Illinois, USA.

Carpenter, S. R., J. F. Kitchell, and J. R. Hodgson. 1985. Cascading trophic interactions and lake productivity. BioScience 35:634-639.

Connell, J. 1961. The influence of interspecific competition and other factors on the distribution of the barnacle Chthamalus stellatus. Ecology 42:710-723.

-----. 1978. Diversity in tropical rainforests and coral reefs. Science 199:1302-1310.

-----. 1983. On the prevalence and importance of interspecific competition: evidence from field experiments. American Naturalist 122:661-696.

Cornell, H. V. 1985a. Local and regional richness of cynipine gall wasps on California oaks. Ecology 66:1247-1260.

-----. 1985b. Species assemblages of cynipid gall wasps are not saturated. American Naturalist 126:565-569.

-----. 1993. Unsaturated patterns in species richness: the role of regional processes in setting local species richness. Pages 243-252 in R. E. Ricklefs and D. Schluter, editors. Species diversity in ecological communities: historical and geographical perspectives. University of Chicago Press, Chicago, Illinois, USA.

Cornell, H. V., and J. H. Lawton. 1992. Species interactions, local and regional processes, and the limits to the richness of ecological communities: a theoretical perspective. Journal of Animal Ecology 61:1-12.

Coyne, J. A. 1994. Ernst Mayr and the origin of species. Evolution 48:19-30.

Cracraft, J. 1982. A nonequilibrium theory for the rate-control of speciation and extinction and the origin of macro-evolutionary patterns. Systematic Zoology 31:348-365.

-----. 1985. Biological diversification and its causes. Annals of the Missouri Botanical Garden 72:794-822.

Crow, J. F., W. R. Engels, and C. Denniston. 1990. Phase three of Wright's shifting-balance theory. Evolution 44:233-247.

Dodson, S. I. 1970. Complementary feeding niches maintained by size-selective predation. Limnology and Oceanography 15:131-137.

-----. 1974. Zooplankton competition and predation: an experimental test of the size-efficiency hypothesis. Ecology 55:605-613.

Drake, J. A. 1991. Community-assembly mechanisms and the structure of an experimental species ensemble. American Naturalist 137:1-26.

Duggins, D. O., and M. N. Dethier. 1985. Experimental studies of herbivory and algal competition in a low intertidal habitat. Oecologia (Berlin) 67:183-191.

Ehrlich, P. R., and P. H. Raven. 1969. Differentiation of populations. Science 165:1228-1232.

Eldredge, N. 1989. Macroevolutionary dynamics: species, niches, and adaptive peaks. McGraw-Hill, New York, New York, USA.

Endler, J. A. 1977. Geographical variation, speciation, and clines. Princeton University Press, Princeton, New Jersey, USA.

-----. 1986. Natural selection in the wild. Princeton University Press, Princeton, New Jersey, USA.

Farrell, B. D., D. E. Dussourd, and C. Mitter. 1991. Escalation of plant defense: do latex and resin canals spur plant diversification? American Naturalist 138:881-900.

Feder, J. L., and G. L. Bush. 1991. Genetic variation among apple and hawthorn host races of Rhagoletis pomonella across an ecological transition zone in the Mid-Western United States. Experimental and Applied Entomology 59:249-265.

Felsenstein, J. 1979. Excursions along the interface between disruptive and stabilizing selection. Genetics 93:773-795.

Fisher, R. A. 1958. The genetical theory of natural selection. Second edition. Dover, New York, New York, USA.

Flecker, A. S. 1992. Fish trophic guilds and the structure of a tropical stream: weak direct vs. strong indirect effects. Ecology 73:927-940.

Futuyma, D. J., and S. S. McCafferty. 1990. Phylogeny and the evolution of host plant associations in the leaf beetle genus Ophraella (Coleoptera: Chrysomelidae). Evolution 44:1885-1913.

Gadgil, M. 1971. Dispersal: population consequences and evolution. Ecology 52:253-261.

Gibson, D. J. 1988. The maintenance of plant and soil heterogeneity in dune grassland. Journal of Ecology 76:497-508.

Goldberg, D. E., and A. M. Barton. 1992. Patterns and consequences of interspecific competition in natural communities: a review of field experiments with plants. American Naturalist 139:771-801.

Gomulkiewicz, R., and R. D. Holt. 1995. When does evolution by natural selection prevent extinction? Evolution 49:201-207.

Grant, V. 1981. Plant speciation. Columbia University Press, New York, New York, USA.

Griffiths, R. W. 1981. The effect of trout predation on the abundance and production of stream insects. Master's thesis. University of British Columbia, Vancouver, British Columbia, Canada.

Hairston, N. G. 1989. Ecological experiments: purpose, design, and execution. Cambridge University Press, New York, New York, USA.

Hall, D. J., W. E. Cooper, and E. E. Werner. 1970. An experimental approach to the production dynamics and structure of freshwater animal communities. Limnology and Oceanography 15:839-928.

Harper, J. L. 1969. The role of predation in vegetational diversity. Brookhaven Symposium in Biology 22:48-62.

Hastings, A. 1983. Can spatial variation alone lead to selection for dispersal? Theoretical Population Biology 24:244-251.

Holt, R. D. 1977. Predation, apparent competition, and the structure of prey communities. Theoretical Population Biology 12:197-229.

-----. 1985. Population dynamics in two-opatch environments: some anomalous consequences of an optimal habitat distribution. Theoretical Population Biology 28:181-208.

-----. 1987. Population dynamics and evolutionary processes: the manifold roles of habitat selection. Evolutionary Ecology 1:331-347.

Hrbacek, J., M. Dvorakova, V. Korlnek and L. Prochazkova. 1961. Demonstration of the effect of the fish stock on the species composition of zooplankton and the intensity of metabolism of the whole plankton association. Internationale Vereinigung fur theoretische und angewandte Limnologie, Verhandlungen 14:192-195.

Humphries, C. J., and L. Parenti. 1986. Cladistic Biogeography. Clarendon Press, Oxford, England.

Huston, M. 1979. A general hypothesis of species diversity. American Naturalist 113:81-101.

Hutchinson, G. E. 1958. Concluding remarks. Cold Spring Harbor Symposia on Quantitative Biology 22:415-427.

-----. 1959. Homage to Santa Rosalia, or why are there so many kinds of animals? American Naturalist 93:145-159.

Jablonski, D. 1986. Background and mass extinctions: the alternation of macroevolutionary regimes. Science 231:129-133.

Jackson, J. B. C. 1974. Biogeographic consequences of eurytopy and stenotopy among marine bivalves and their evolutionary significance. American Naturalist 108:541-560.

Kalisz, S. 1986. Variable selection on the timing of germination in Collinsia verna (Scrophulariaceae). Evolution 40:479-491.

King, R. B. 1994. Color-pattern variation in Lake Erie water snakes: prediction and measurement of natural selection. Evolution 47:1819-1833.

Kodric-Brown, A., and J. H. Brown. 1984. Truth in advertising: the kinds of traits favored by natural selection. American Naturalist 124:309-323.

Kohler, S. L., and M. A. McPeek. 1989. Predation risk and the foraging behavior of competing stream insects. Ecology 70:1811-1825.

Krebs, C. J. 1994. Ecology: the experimental analysis of distribution and abundance. Fourth edition. Harper Collins, New York, New York, USA.

Kuno, E. 1981. Dispersal and the persistence of populations in unstable habitats: a theoretical note. Oecologia (Berlin) 49:123-126.

Lande, R. 1979. Quantitative genetic analysis of multivariate evolution, applied to brain:body size allometry. Evolution 33:402-416.

-----. 1980. Genetic variation and phenotypic evolution during allopatric speciation. American Naturalist 116:463-479.

-----. 1981. Models of speciation by sexual selection on polygenic traits. Proceedings of the National Academy of Sciences (USA) 78:3721-3725.

Lande, R., and M. Kirkpatrick. 1988. Ecological speciation by sexual selection. Journal of Theoretical Biology 133:85-98.

Lawlor, S. P., and P. J. Morin. 1993. Food web architecture and population dynamics in laboratory microcosms of protists. American Naturalist 141:675-686.

Lawton, J. H., and R. M. May. 1995. Extinction rates. Oxford University Press, Oxford, England.

Levins, R. 1964. The theory of fitness in a heterogeneous environment. IV. The adaptive significance of gene flow. Evolution 18:635-638.

-----. 1968. Evolution in changing environments. Princeton University Press, Princeton, New Jersey, USA.

Lubchenco, J. 1978. Plant species diversity in a marine intertidal community: importance of herbivore food preference and algal competitive abilities. American Naturalist 112:23-39.

-----. 1980. Algal zonation in the New England rocky intertidal community: an experimental analysis. Ecology 61:333-344.

Lynch, J. D. 1989. The gauge of speciation: on the frequencies of modes of speciation. Pages 527-553 in D. Otte and J. A. Endler, editors. Speciation and its consequences. Sinauer, Sunderland, Massachusetts, USA.

MacArthur, R. H. 1972. Geographical ecology. Princeton University Press, Princeton, New Jersey, USA.

MacArthur, R. H., and E. O. Wilson. 1967. The theory of island biogeography. Princeton University Press, Princeton, New Jersey, USA.

May, R. M. 1973. Stability and complexity in model ecosystems. Princeton University Press, Princeton, New Jersey, USA.

Mayr, E. 1942. Systematics and the origin of species. Columbia University Press, New York, New York, USA.

-----. 1963. Animal species and evolution. Belknap Press of Harvard University, Cambridge, Massachusetts, USA.

McPeek, M. A. 1990. Determination of species composition in the Enallagma damselfly assemblages of permanent lakes. Ecology 71:83-98.

-----. 1995a. Testing hypotheses about evolutionary change on single branches of a phylogeny using evolutionary contrasts. American Naturalist 145:686-703.

-----. 1995b. Morphological evolution mediated by behavior in the damselflies of two communities. Evolution 49:749-769.

McPeek, M. A., and R. D. Holt. 1992. The evolution of dispersal in spatially and temporally varying environments. American Naturalist 140:1010-1027.

McQueen, D. J., M. R. S. Johannes, J. R. Post, T. J. Stewart, and D. R. S. Lean. 1989. Bottom-up and top-down impacts on freshwater pelagic community structure. Ecological Monographs 59:289-308.

McQueen, D. J., J. R. Post, E. L. Mills. 1986. Trophic relationships in freshwater pelagic ecosystems. Journal of the Fisheries Research Board of Canada 43:1571-1581.

Miller, T. E. 1987. Effects of emergence time on survival and growth in an early old-field plant community. Oecologia (Berlin) 72:272-278.

Miller, T. E., A. A. Winn, and D. E. Schemske. 1994. The effects of density and spatial distribution on selection for emergence time in Prunella vulgaris (Lamiaceae). American Journal of Botany 81:1-6.

Mitter, C., B. F. Farrell, and B. Wiegmann. 1988. The phylogenetic study of adaptive zones: has phytophagy promoted insect diversification? American Naturalist 132:107-128.

Moran, N. A. 1992. The evolutionary maintenance of alternative phenotypes. American Naturalist 139:971-989.

Neill, W. E. 1975. Experimental studies of microcrustacean competition, community composition and efficiency of resource utilization. Ecology 56:809-826.

Paine, R. T. 1966. Food web complexity and species diversity. American Naturalist 100:65-75.

-----. 1969. A note on trophic complexity and community stability. American Naturalist 103:91-93.

-----. 1974. Intertidal community structure: experimental studies on the relationship between a dominant competitor and its principle predator. Oecologia 15:93-120.

-----. 1980. Food webs: linkage, interaction strength and community infrastructure. Journal of Animal Ecology 49:667-685.

-----. 1988. Food webs: road maps of interactions or grist for theoretical development? Ecology 69:1648-1654.

Phillips, P. C. 1994. Peak shifts and polymorphisms during phase three of Wright's shifting-balance process. Evolution 47:1733-1743.

Pimm, S. L. 1978. Sympatric speciation: a simulation model. Biological Journal of the Linnean Society 11:131-139.

Platnick, N. I., and G. Nelson. 1978. A method of analysis for historical biogeography. Systematic Zoology 27:1-16.

Post, J. R., and D. Cucin. 1984. Changes in the benthic community of a small precambrian lake following the introduction of yellow perch, Perca flavescens. Canadian Journal of Fisheries and Aquatic Sciences 41:1496-1501.

Rice, W. R. 1985. Disruptive selection on habitat preference and the evolution of reproductive isolation: an exploratory experiment. Evolution 38:735-742.

-----. 1987. Speciation via habitat specialization: the evolution of reproductive isolation as a correlated character. Evolutionary Ecology 1:301-314.

Rice, W. R., and E. E. Hostert. 1993. Laboratory experiments on speciation: what have we learned in 40 years? Evolution 47:1637-1653.

Ricklefs, R. E. 1987. Community diversity: relative roles of local and regional processes. Science 235:167-171.

-----. 1989. Speciation and diversity: the integration of local and regional processes. Pages 599-622 in D. Otte and J. A. Endler, editors. Speciation and its consequences. Sinauer, Sunderland, Massachusetts, USA.

-----. 1990. Ecology. Third edition. W. H. Freeman, New York, New York, USA.

Ricklefs, R. E., and D. Schluter. 1993. Species diversity in ecological communities: historical and geographical perspectives. University of Chicago Press, Chicago, Illinois, USA.

Robinson, B. W., and D. S. Wilson 1994. Character release and displacement in fishes: a neglected literature. American Naturalist 144:596-627.

Robinson, J. V., and J. E. Dickerson. 1987. Does invasion sequence affect community structure? Ecology 68:587-595.

Rosenzweig, M. L. 1975. On continental steady states of species diversity. Pages 121-141 in M. L. Cody and J. M. Diamond, editors. Ecology and evolution of communities. Harvard University Press, Cambridge, Massachusetts, USA.

-----. 1978. Competitive speciation. Biological Journal of the Linnean Society 10:274-289.

Rummell, J. D., and J. D. Roughgarden. 1985. A theory of faunal buildup for competition communities. Evolution 39:1009-1033.

Sanders, H. L. 1968. Marine benthic diversity: a comparative study. American Naturalist 102:243-282.

Schluter, D., and J. D. MacPhail. 1993. Character displacement and replicate adaptive radiation. Trends in Ecology and Evolution 8:197-200.

Schoener, T. W. 1983. Field experiments on interspecific competition. American Naturalist 122:240-285.

-----. 1986. Mechanistic approaches to community ecology: a new reductionism? American Zoologist 26:81-106.

Sih, A. 1980. Optimal behavior: can foragers balance two conflicting demands? Science 210:1041-1043.

-----. 1982. Foraging strategies and the avoidance of predation by an aquatic insect, Notonecta hoffmanni. Ecology 63:786-796.

Sih, A., P. Crowley, M. McPeek, J. Petranka, and K. Strohmeier. 1985. Predation, competition, and prey communities: a review of field experiments. Annual Review of Ecology and Systematics 16:269-311.

Simpson, G. G. 1953. The major features of evolution. Columbia University Press, New York, New York, USA.

Slobodkin, L. B., and H. L. Sanders. 1969. On the contribution of environmental predictability to species diversity. Brookhaven Symposium in Biology 22:82-95.

Smith-Gill, S. J. 1983. Developmental plasticity: developmental conversion versus phenotypic modulation. American Zoologist 23:47-55.

Soule, M. E. 1987. Viable populations for conservation. Cambridge University Press, Cambridge, United Kingdom.

Sprules, W. G. 1972. Effects of size-selective predation and food competition on high altitude zooplankton communities. Ecology 53:375-386.

Stanley, S. M. 1979. Macroevolution: pattern and process. W. H. Freeman, San Francisco, California, USA.

Stemberger, R. S., and J. M. Lazorchak. 1994. Zooplankton assemblage responses to disturbance gradients. Canadian Journal of Fisheries and Aquatic Science 51:2435-2447.

Stratton, D. A. 1992. Life-cycle components of selection in Erigeron annuus: I. phenotypic selection. Evolution 46:92-106.

Strong, D. R., J. H. Lawton, and R. Southwood. 1984. Insects on plants: community patterns and mechanisms. Harvard University Press, Cambridge, Massachusetts, USA.

Sultan, S. E. 1987. Evolutionary implications of phenotypic plasticity in plants. Evolutionary Biology 21:127-178.

Tauber, C. A., and M. J. Tauber. 1989. Sympatric speciation in Insects: perception and perspective. Pages 307-344 in D. Otte and J. A. Endler, editors. Speciation and its consequences. Sinauer, Sunderland, Massachusetts, USA.

Tessier, A. J., and J. Welser. 1991. Cladoceran assemblages, seasonal succession and the importance of a hypolimnetic refuge. Freshwater Biology 25:85-93.

Thornhill, R., and J. Alcock. 1983. The evolution of insect mating systems. Harvard University Press, Cambridge, Massachusetts, USA.

Tilman, D. 1982. Resource competition and community structure. Princeton University Press, Princeton, New Jersey, USA.

-----. 1987. The importance of the mechanisms of interspecific competition. American Naturalist 129:769-774.

-----. 1988. Plant strategies and the dynamics and structure of plant communities. Princeton University Press, Princeton, New Jersey, USA.

Travis, J. 1990. The interplay of population dynamics and the evolutionary process. Philosophical Transactions of the Royal Society of London, B 330:253-259.

Travis, J., W. H. Keen, and J. Juilianna. 1985. The effects of multiple factors on viability selection in Hyla gratiosa tadpoles. Evolution 39:1087-1099.

Turner, T. 1985. Stability of rocky intertidal surfgrass beds: persistence, preemption, and recovery. Ecology 66:83-92.

van der Toorn, J., and T. L. Pons. 1988. Establishment of Plantago lanceolata L. and Plantago major L. among grass: II. Shade tolerance of seedlings and selection on time of germination. Oecologia (Berlin) 76:341-347.

Vanni, M. J. 1986. Competition in zooplankton communities: suppression of small species by Daphnia pulex. Limnology and Oceanography 31:1039-1056.

-----. 1988. Freshwater zooplankton community structure: introduction of large invertebrate predators and large herbivores to a small-species community. Canadian Journal of Fisheries and Aquatic Sciences 45:1758-1770.

Via, S., and R. Lande. 1985. Genotype-environment interaction and the evolution of phenotypic plasticity. Evolution 39:505-522.

Wade, M. J., and S. Kalisz. 1990. The causes of natural selection. Evolution 44:1947-1955.

Weis, A. E., W. G. Abrahamson, and M. C. Anderson. 1992. Variable selection on Eurosta's gall size. I. The extent and nature of variation in phenotypic selection. Evolution 46:1674-1697.

Werner, E. E., and B. R. Anholt. 1993. Ecological consequences of the trade-off between growth and mortality rates mediated by foraging activity. American Naturalist 142:242-272.

Werner, E. E., and M. A. McPeek. 1994. The roles of direct and indirect effects on the distributions of two frog species along an environmental gradient. Ecology 75:1368-1382.

West-Eberhard, M. J. 1983. Sexual selection, social competition, and speciation. Quarterly Review of Biology 58:155-183.

Whittaker, J. H. 1975. Communities and ecosystems. Second edition. Macmillan, New York, New York, USA.

Wilbur, H. M. 1984. Complex life cycles and community organization in amphibians. Pages 196-224 in P. W. Price, C. N. Slobodchikoff and W. S. Gaud, editors. A new ecology: novel approaches to interactive systems. John Wiley & Sons, New York, New York, USA.

Wilson, D. S. 1989. The diversification of single gene pools by density- and frequency-dependent selection. Pages 366-385 in D. Otte and J. A. Endler, editors. Speciation and its consequences. Sinauer, Sunderland, Massachusetts, USA.

Wilson, D. S., and M. Turelli. 1986. Stable underdominance and the evolutionary invasion of empty niches. American Naturalist 127:835-850.

Wright, S. 1932. The roles of mutation, inbreeding, cross-breeding and selection in evolution. Proceedings of the Sixth International Congress on Genetics 1:356-366.

Zaret, T. M. 1980. Predation and freshwater communities. Yale University Press, New Haven, Connecticut, USA.


Ms. Lima Biology Teacher

You need to know the conditions required for natural selection to occur. These include: overproduction of offspring, inherited variation, and the struggle to survive, which result in differential reproductive success.

Evolution is a change in the characteristics of a population from one generation to the next.

Darwin proposed that evolution happened due to natural selection. Natural selection is the process by which individuals that have favorable variations and are better adapted to their environment survive and reproduce more successfully than less well adapted individuals do.

Over many generations, natural selection can result in the evolution of new species, which is called speciation.

&ldquoSURVIVAL OF THE FITTEST&rdquo organism&rsquos best suited to their environment survive and reproduce


Natural Selection is based on four main principles:


1. Overproduction of offspring: Each species produces more individuals than can survive to maturity most offspring are lost to predators, disease or other factors.


2. Variation: Genetic variation exists within populations. The individuals of a population may differ in traits such as size, color, strength, speed, ability to find food, or resistance to certain diseases. These variations are inheritable traits.


3. Struggle to survive: The amount of space, food and other resource in nature is finite. Organisms must compete for limited resources. Also, some individuals will be harmed by predation, disease, or unfavorable conditions.


4. Adaptation: Individuals whose traits are best suited for their environment are more likely to survive, produce more offspring and pass their traits to the future generation than individuals that lack those traits. Over time, those traits become more frequent in the population