EVOLUTION INTERNATIONAL JOURNAL OF ORGANIC EVOLUTION

Size: px
Start display at page:

Download "EVOLUTION INTERNATIONAL JOURNAL OF ORGANIC EVOLUTION"

Transcription

1 EVOLUTION INTERNATIONAL JOURNAL OF ORGANIC EVOLUTION PUBLISHED BY THE SOCIETY FOR THE STUDY OF EVOLUTION Vol. 57 Noveber 003 No. 11 Evolution, 57(11), 003, pp SEXUAL DIMORPHISM AND ADAPTIVE SPECIATION: TWO SIDES OF THE SAME ECOLOGICAL COIN DANIEL I. BOLNICK 1 * AND MICHAEL DOEBELI * 1 Section o Evolution and Ecology, Center or Population Biology, Storer Hall, University o Caliornia, Davis, Caliornia E-ail: dibolnick@ucdavis.edu Departent o Zoology, University o British Colubia, 670 University Boulevard, Vancouver, British Colubia V6T 1Z4, Canada E-ail: doebeli@zoology.ubc.ca Abstract. Models o adaptive speciation are typically concerned with deonstrating that it is possible or ecologically driven disruptive selection to lead to the evolution o assortative ating and hence speciation. However, disruptive selection could also lead to other ors o evolutionary diversiication, including ecological sexual diorphiss. Using a odel o requency-dependent intraspeciic copetition, we show analytically that adaptive speciation and diorphis require identical ecological conditions. Nuerical siulations o individual-based odels show that a single ecological odel can produce either evolutionary outcoe, depending on the genetic independence o ale and eale traits and the potential strength o assortative ating. Speciation is inhibited when the genetic basis o ale and eale ecological traits allows the sexes to diverge substantially. This is because sexual diorphis, which can evolve quickly, can eliinate the requency-dependent disruptive selection that would have provided the ipetus or speciation. Conversely, populations with strong assortative ating based on ecological traits are less likely to evolve a sexual diorphis because eales cannot siultaneously preer ales ore siilar to theselves while still allowing the ales to diverge. This conlict between speciation and diorphis can be circuvented in two ways. First, we ind a novel or o speciation via negative assortative ating, leading to two diorphic daughter species. Second, i assortative ating is based on a neutral arker trait, trophic diorphis and speciation by positive assortative ating can occur siultaneously. We conclude that while adaptive speciation and ecological sexual diorphis ay occur siultaneously, allowing or sexual diorphis restricts the likelihood o adaptive speciation. Thus, it is iportant to recognize that disruptive selection due to requency-dependent interactions can lead to ore than one or o adaptive splitting. Key words. Adaptive dynaics, disruptive selection, evolutionary branching, resource partitioning, stable itness inia, sypatric speciation. Traditionally, evolutionary biologists have thought that speciation is initiated by a phase o geographic isolation between subpopulations o an ancestral lineage (Mayr 1963). Over evolutionary tie, these allopatric populations diverge genetically, either in response to drit or dierent selection regies. As a by-product o the dierent evolutionary trajectories, the two eerging species becoe reproductively isolated. Even though adaptations ay be the cause o the dierentiation in such allopatric speciation scenarios, the initial process o splitting the gene pool is not itsel adaptive and instead is generated by external orces leading to geographic isolation. In contrast, the past years have seen a renewed interest in a process tered adaptive speciation, in which the split- * Both authors contributed equally to this paper. 003 The Society or the Study o Evolution. All rights reserved. Received October 9, 00. Accepted May 9, ting itsel is an adaptation (Dieckann et al. 003). This interest has been spurred on the one hand by a nuber o epirical studies suggesting that speciation can occur under nonallopatric conditions (e.g., Schliewen et al. 1994; Bernatchez et al. 1996; Shaw et al. 000; Wilson et al. 000; Schliewen et al. 001; Via 001), and on the other hand by theoretical advances showing that adaptive speciation is a theoretically plausible process (reviewed in Turelli et al. 001). Theoretical odels o adaptive speciation ust speciy the ecological echaniss generating the disruptive selection regie that renders the splitting adaptive. Under the classical view o static itness landscapes, disruptive selection (e.g., through biodal niches) is unlikely to be iportant or adaptive splitting because a population whose ean phenotype is close to a itness iniu will siply evolve directionally

2 434 D. I. BOLNICK AND M. DOEBELI away ro it, aking evolutionary diversiication unlikely. In contrast, requency-dependent interactions induce itness landscapes that change dynaically in response to changes in the phenotype distribution. In particular, i disruptive selection is generated by requency-dependent interactions, a perturbation to the ean phenotype away ro a itness iniu can induce changes in the itness landscape that drive the population back toward the state in which itness turns disruptive. Such evolutionary stability o itness inia has been ound in several dierent odels (e.g., Eshel 1983; Brown and Pavlovic 199; Abras et al. 1993; Christiansen 1991; Geritz et al. 1998; Doebeli and Dieckann 000; Doebeli and Dieckann 003). Consequently, odels o adaptive speciation typically involve requency-dependent intraspeciic interactions. In asexual odels, the process o convergence to a regie o disruptive selection is oten ollowed by adaptive splitting into separate lineages. This phenoenon is called evolutionary branching in the theoretical raework o adaptive dynaics, an analytic approxiation or the evolution o ean phenotypes (Metz 1996; Geritz et al. 1998). An iportant insight gained ro adaptive dynaics theory is that evolutionary branching is a generic and robust phenoenon in any dierent odels o evolution due to requency-dependent ecological interactions (e.g., Geritz et al. 1998; Kisdi 1999; Doebeli and Dieckann 000, 003). The ost coon ecological setting used to illustrate evolutionary branching entails requency-dependent copetition or a liiting resource. In the corresponding odels, populations typically evolve under directional selection toward the phenotype best suited to the ost abundant resource, the density-dependent optiu (Bolnick 001). Once there, this ost coon phenotype experiences disproportionately intense copetition, and hence has lowest itness. Accordingly, such odels readily exhibit evolutionary branching in clonal populations (Dieckann and Doebeli 1999; Kisdi and Geritz 1999; Doebeli and Dieckann 000). In sexual populations, however, adaptive splitting requires assortative ating echaniss that prevent the production o phenotypically interediate ospring. Consequently, a priary ai o recent odels o adaptive speciation has been to deonstrate that the eergence o disruptive selection can avor the evolution o assortative ating and subsequent evolutionary branching in sexual populations (Dieckann and Doebeli 1999; Doebeli and Dieckann 000, 003). However, adaptive speciation is not the only possible outcoe o convergence toward disruptive selection. Other evolutionary echaniss can widen the phenotypic distribution o the population, equalizing the eects o copetition (and hence equalizing itness) across all phenotypes (Roughgarden 197). In particular, adaptive splitting can occur intraspeciically, as seen in ontogenetic niche shits, resource polyorphiss, and ecological sexual diorphiss (Slatkin 1984). By lattening the itness unction, these alternative ors o phenotypic expansion ay eliinate the disruptive orce that would have driven speciation. It thus becoes iportant to understand the genetic conditions that ay give rise to alternative escape routes ro stable itness inia and the relative rates with which dierent alternatives ight evolve. In this paper we deonstrate that a single odel o intraspeciic copetition can give rise to ecological sexual diorphis and/or adaptive speciation, and we explore how ating behavior and genetic assuptions about trait deterination in ales and eales aect the relative likelihood o these two outcoes. Using an adaptive dynaics odel or quantitative traits in ales and eales deterining copetition or a liiting resource, we irst show that requencydependent copetition can avor an ecological sexual diorphis and that the ecological conditions or evolutionary branching and or sexual diorphis are identical. We then use individual-based odels incorporating explicit genetics and assortative ating to exaine the prerequisites or sexual diorphis and speciation. DETERMINISTIC MODEL OF SEXUAL DIMORPHISM In Slatkin s (1984) quantitative genetic odels sexual diorphis is a consequence o copetitive displaceent, and the ecological echaniss driving evolutionary change bear a striking reseblance to odels o adaptive speciation (e.g., Doebeli 1996; Dieckann and Doebeli 1999). Here we present a deterinistic odel o sexual diorphis using the sae underlying ecological dynaics as in Slatkin (1984) and Dieckann and Doebeli (1999). The resulting equations serve as the basis or the individual-based odels used in subsequent sections to exaine the interaction between diorphis and speciation. Males and eales are characterized by a quantitative character z (e.g., body size) that deterines ecological interactions, denoted by z in ales and by z in eales. To derive the deterinistic dynaics, we assue that there is no genetic covariance between z and z, or exaple, the ecological trait z is deterined by independent sets o loci in ales and eales. We assue that ales pass on their phenotype to sons and eales pass on their phenotype to daughters, so the value o a parent s trait is only iportant to progeny o the sae sex. Resources are ost abundant or individuals with soe interediate character value z 0, which we arbitrarily set at z 0 0. Speciically, we assue that populations that are onoorphic or character value z have carrying capacity [ ] (z z 0) K(z) K0exp. (1) k Here K 0 scales the axial carrying capacity, and k easures how ast resource availability decreases with increasing phenotypic distance ro the optial trait value z 0. To incorporate requency-dependence, the driving orce o copetitive displaceent, we assue that the strength o copetition between individuals with phenotypes z and z decreases with phenotypic distance and is given by [ ] (z z) c(z, z) exp, () c where c easures how ast copetitive ipacts decrease with an increase in the phenotypic distance between interacting individuals. Thus, c deterines the strength o requency dependence in the copetitive interactions, with sall c corresponding to a high degree o requency de-

3 SEXUAL DIMORPHISM AND ADAPTIVE SPECIATION 435 pendence. Note that we assue that the carrying capacity (eq. 1) and eects o copetition between two individuals (eq. ) are independent o the sex o the copeting individuals. Deterinistic adaptive dynaics odels assue that evolution is utation liited and that the phenotype distribution o a resident population deterines the invasion success o new utants (Dieckann and Law 1996; Metz et al. 1996; Geritz et al. 1998). We irst calculate the ecological equilibriu population sizes or a population in which eales and ales are each onoorphic or soe trait value z and z, respectively. Based on this equilibriu state, on the carrying capacity unction K(z), equation (1), and on the copetition unction c(z, z), equation (), we then calculate the per capita growth rate o any given rare utant phenotype in either ales or eales. In the liit o very sall utations, these growth rates yield selection gradients in both ales and eales, ro which the adaptive dynaics are deduced. Here we assue that the underlying odel or the ecological dynaics is a discrete-tie odel with nonoverlapping generations given by the Beverton-Holt equation, rn(t) n(t 1), (3) r 1 1 n(t) K where n(t) and n(t 1) are population densities in successive generations, r is the per capita nuber o ospring, and K is the carrying capacity. In the Appendix, we describe how this odel can be adopted to describe the dynaics o ale and eale population densities and calculate equilibriu population densities o onoorphic ales and eales. Using these equilibriu densities, one can calculate the growth rates o rare utant ales and eales in a resident population (z,z ), which are given by two unctions w ( z, z, z ) or utant ales z and w ( z, z, z ) or utant e- ales z (see Appendix). Fro these growth rates, one obtains the selection gradients or ale and eale traits in a resident population (z,z )as w g (z, z ) and (4a) dz z z w g (z, z ). (4b) dz z z These gradients describe the adaptive dynaics o the ale and eale traits z and z. In particular, equilibriu points o the adaptive dynaics are points z*, z* in phenotype space at which the gradients g and g vanish siultaneously. It is shown in the Appendix that the point ( z*, z* ) (0,0) is always an equilibriu point o the adaptive dynaics (recall that we assued that z 0 0 is the trait value axiizing the carrying capacity). This equilibriu (0, 0) is locally stable i and only i c k, where k and c are the paraeters deterining the width o the carrying capacity unction, equation (1), and the strength o requency dependence in the copetition unction, equation (), respectively. Thus, i the eect o requency dependence is weak relative to the stabilizing selection iposed by the uniodal resource distribution, both sexes will adapt to the odal resource and no diorphis will occur. We note that i the equilibriu ( z*, z* ) (0,0) is locally stable or the adaptive dynaics, then it is also evolutionarily stable in the sense that the invasion itness unctions w and w have a axiu with respect to the utant trait values at the equilibriu. Conversely, i requency dependence is relatively strong ( c k ), then the syetric equilibriu (0,0) is unstable, and instead there is a new equilibriu ( z*, z* ) o the adaptive dynaics given by 1 z* z* log k c 1. (5) This equilibriu represents a sexual diorphis, and it exists i and only i c k. (6) I the diorphic equilibriu exists, then so does the equilibriu with the ale and eale trait values reversed, and both equilibria are locally stable. Note that inequality (6) is essentially the sae condition as that ound by Slatkin (1984) or the evolution o sexual diorphis, naely V k c, where V is the phenotypic variance. In the present odel V 0 because o our assuption, necessary to derive the adaptive dynaics, that each sex is onoorphic. With V 0, Slatkin s (1984) condition and condition (6) above are identical. Our analysis also conirs Slatkin s (1984) conjecture that i the syetric equilibriu ( z*, z* ) (0,0) is unstable, then there is a stable asyetric equilibriu ( z*, z* ) given by equation (5), inducing convergence o the evo- lutionary dynaics toward a sexually diorphic state. It is iportant to note, however, that while this equilibriu is an attractor in the two-diensional phenotype space o ale and eale trait values, the equilibriu is not evolutionarily stable. This can be seen by considering the second derivatives o the itness unctions w and w with respect to utant trait values: one can show that both these unctions actually have a iniu at the equilibriu (5) whenever this equilibriu exists. In other words, the diorphic equilibria are theselves potential evolutionary branching points or urther niche partitioning. Nevertheless, the traits will not undergo evolutionary branching in randoly ating populations, or which the diorphic equilibriu (5) thereore represents the evolutionary end state. However, evolutionary branching could occur in principle when ating is assortative. This is exepliied by odels o adaptive speciation (Dieckann and Doebeli 1999). These speciation odels use the sae basic ecological assuptions as the diorphis odel above, but they are dierent in that ales and eales are assued to always have identical ecological phenotypes but ay exhibit nonrando ating. Thus, sexual diorphis and adaptive speciation are expected to occur under siilar ecological conditions, but or dierent genetic assuptions. There are two ain reasons why one ight expect that the two processes would be utually exclusive. First, whichever or o divergence evolves irst would tend to eliinate the disruptive selection necessary to drive the other. Second, positive assortative ating, which is generally deeed necessary or speciation, ight be incopatible with diorphis as long as it is based on ale and eale siilarity in ecological c

4 436 D. I. BOLNICK AND M. DOEBELI traits. Nevertheless, the act that the diorphic equilibriu (5) is an evolutionary branching point could lead to interesting interactions between sexual diorphis and assortative ating. To explore these issues we develop an individual-based nuerical odel with explicit genetics in which both processes can be studied siultaneously. STOCHASTIC MODEL OF SEXUAL DIMORPHISM We irst assue that ating is rando and concentrate on the dynaics o sexual diorphis using individual-based odels with explicit ultilocus genetics. As beore, the population is subject to the ecological dynaics in equations (1 3). Rather than siply assuing each sex is onoorphic, however, each individual is now assigned a genotype that in turn deterines its ecological trait value. In their nuerical odels o sypatric speciation, Dieckann and Doebeli (1999) assigned each diploid individual N loci o equal additive eect. Each locus had two alleles, with phenotypic value 1 or 1. An individual s phenotype value was the su o the additive values o all N alleles, ranging ro N to N. We reer to this as the basic ultilocus approach and use it later in this paper to odel the degree o assortative ating and an unlinked ating phenotype. However, this approach is insuicient or odeling sexual diorphis, because it does not allow one to vary the degree to which ale and eale phenotypes are genetically independent. To odel sexual diorphis, we used a siilar additive diploid ultilocus approach but incorporated loci that are only expressed in one sex or another. The total nuber o loci expressed by any one individual (N total ) can be divided into those loci that are expressed in both sexes (N shared ) and those that are only expressed in ales (N ale ) or eales (N eale ), so N total N shared N ale N shared N eale. This schee relects recent quantitative trait loci (QTL) studies o sexually diorphic quantitative traits that have revealed nuerous sex-speciic QTL (Mogil et al. 1997; Nuzhdin et al. 1997; Agulnik et al. 1998; Gurganus et al. 1999; Raos et al. 1999; Kopp et al. 003). We assue that N ale N eale so that N total is the sae or both sexes. As with the basic odel, each locus has two alleles, with allele j at locus i having two possible values: 1 locusij (7) 1. The value o an individual s ecological phenotype is then the su o the allele values at all the loci that the individual expresses (shared loci plus the loci or the relevant sex): Nshared Nale z locus locus and (8) i j ij i j ij Nshared Neale z locus locus. (9) i j ij i j ij Phenotypes ay range ro N total to N total. In the siulations we standardized the range o traits ro 1 to1, or exaple, we divided the values obtained ro equations (8) and (9) by N total. This schee or explicitly odeling ale and eale ecological character values allows us to anipulate a population s genetic capacity or sexual diorphis. When N shared N total, there are no sex-speciic loci, and hence ale and eale trait eans cannot possibly diverge. As N shared becoes saller the sexes can diverge ore, until their traits are copletely independent at N shared 0. Hence by anipulating the proportion o shared loci (N shared /N total )wecan control a population s potential or sexual diorphis. For the nuerical siulations, we initialize populations by assigning individuals a sex and a genotype, which in turn deterines the individuals ecological phenotype. The distribution o the ecological phenotypes then deterines individual survival probabilities, and hence the ecological dynaics o the population. At each tie step t, each individual survives with probability 1 P(z), (10) r 1 1 n e,z(t) K(z) where z is the individual s trait value, K(z) is the carrying capacity o the phenotype (eq. 1), and n e,z (t) is the eective population size that the individual experiences in the current population. Using the copetition unction c(z, z), equation (), this eective density is calculated as n (t) c(z, z)n (t), (11) e,z z where the su runs over all possible trait values z, and where n z (t) is the nuber o individuals with trait value z. Note that, in slight abuse o notation, we now use the sybol n to denote actual population size rather than population density, because in the individual-based odels we are dealing with actual nubers o individuals. Note also that n e,z (t) includes both ales and eales. Each o the surviving eales reproduces by randoly choosing one o the surviving ales as a ate and then producing a nuber o ospring drawn ro a Poisson distribution with ean r. The genotype o each ospring is deterined probabilistically ro the parent genotypes under the assuptions o Mendelian segregation within loci and ree recobination between loci. Each allele in the ospring has a probability o reversing its value due to utation. This unusually high utation rate was chosen to speed up the siulations. (We note that our genetic architecture can be understood ore generally as describing independent stretches o DNA o variable length that aect the trait under consideration additively and that recobine reely with other such stretches o DNA. In particular, such stretches ight be uch longer than a single locus, hence the utation rate per such stretch ight be quite high.) The ospring is randoly ade ale or eale with equal probability, which then deterines the subset o loci it will use to express its ecological trait z. The resulting population o ospring is then subjected again to ecological dynaics and ating, and this generational cycle is repeated iteratively. An exaple o the evolutionary dynaics o ale and eale trait values eerging ro this individual-based odel is shown in Figure 1 or a case when N shared /N total 0.4. The population was initialized with all individuals having an ecological phenotype o z 1 (all loci ixed with z

5 SEXUAL DIMORPHISM AND ADAPTIVE SPECIATION 437 FIG. 1. Siulation o the evolution o sexual diorphis as ale (A) and eale (B) phenotype distributions change over tie in response to resource copetition. Darker shading indicates a greater nuber o individuals o a given phenotype at a given tie. The horizontal line at 0.0 in (A) and (B) indicates the location o the axiu o the carrying capacity curve. Fitness unctions are shown or generation 10 (C), 00 (D), and 400 (E), with the ean phenotypes or ales ( ) and eales (). The dashed vertical line arks the onset o sexual diorphis. Both sexes were initially onoorphic or the ecological trait z 1.0. N shared /N total 0.4, s 10, K , k 1.0, c 0.5, r 5, 0.001, N total 10, N assort 5. allele values o 1), and both ales (Fig. 1A) and eales (Fig. 1B) quickly evolved under directional selection (Fig. 1C) toward the density-dependent phenotypic optiu o z 0. As the population ean approached this optiu, it cae under disruptive selection due to requency-dependent copetition (Fig. 1D). A sexual diorphis then evolved (Fig. 1A, B), lattening the itness unction so that all phenotypes had nearly equal itness (Fig. 1E). Siilar dynaics are seen or any run in which c k and N shared / N total is less than one. The direction o the resulting diorphis (z z or z z ) is arbitrary and varies between replicate siulations. The degree o sexual diorphis that results ro disruptive selection is sensitive to two sets o paraeters. The ecological paraeters k and c deterine the location o the diorphic equilibriu given by equation (5), to which ales and eales will evolve in the nongenetic, analytical odel o the previous section. However, in the genetic in-

6 438 D. I. BOLNICK AND M. DOEBELI FIG.. The agnitude o ecological sexual diorphis depends on the proportion o loci shared between ales and eales (N shared / N total ).The agnitude o diorphis is easured by the absolute value o Student s t-statistic. The horizontal line at t indicates the cut-o below which diorphis is not statistically signiicant. Paraeter values were: s 10, K , k 0.75, c 0.5, r 5, 0.001, N total 10, N assort 5, with 10 replicates or each value o N shared /N total, run or 1000 generations each. dividual-based odel, N shared /N total can constrain whether the sexes are able to evolve to these values, as illustrated in Figure. When between-sex covariance is high, the sexes are unable to diverge and so the population reains at the interediate phenotype value z 0, subject to a stable itness iniu. Such persistent disruptive selection is the starting point or adaptive speciation (Dieckann and Doebeli 1999). In the next section we incorporate assortative ating echaniss into our individual-based odel to illustrate that when N shared / N total 1 the population can escape ro the itness iniu via speciation. We then cobine the assortative ating odel with variable values o N shared /N total to investigate how speciation and sexual diorphis interact. STOCHASTIC MODEL OF ADAPTIVE SPECIATION As beore, all individuals possess an ecological phenotype deterined by the additive eect o N total diallelic loci. The ecological dynaics reain the sae, but in contrast to the preceding section, N shared N total so diorphis is ipossible, and eales ay choose their ate nonrandoly. Assortative ating is described by a ate-choice unction (Fig. 3) that deterines the probability o a given eale accepting a given ale as a ate. Feales vary with respect to a new quantitative genetic trait or assortability, a, which deterines the degree to which a eale ates assortatively. As with the ecological trait, the value o a represents the su o allele values o N assort independent diallelic loci, standardized to range ro 1 to 1. While the N assort loci are present in both ales and eales and inherited according to noral Mendelian rules, only eales express their assortability, in keeping with eale-liited ating (see Appendix). Negative values o a coner disassortative ating, positive values lead to positive assortative ating, and values near zero produce rando ating. The probability that a eale with assortative phenotype a and ecological trait z will ate with a ale with ecological trait z is described by the ollowing ate-choice unction (Fig. 3): P(a, z, z ) [ ] 1 a exp z z or a 0 s 1 or a 0 (1) [ 1 a ] exp ( z z ) or a 0. s Here s is a scaling paraeter that deterines the slope o the ate-choice unction. Large values o s latten the unction P(a, z,z ) or all a (Fig. 3B), so that all phenotypes are equally acceptable, in which case even eales with assortative trait values a close to 1 or 1 will ate randoly. As s decreases, the probability that a eale ates with a phenotypically dierent (phenotypically siilar) ale drops o ore and ore rapidly or eales with positive (negative) values o a (see Fig. 3A). In the nuerical siulations, we assued that every surviving eale ates, iplying that the ate-choice unction (1) only deterines the relative probabilities with which each ale is chosen by a particular eale. Thus, we assued that there is no cost to a eale or assortative ating (see Discussion), though ales with rare ecological phenotypes are penalized. Siulations in which diorphis was restricted (i.e., N shared /N total 1), and eales initially ated randoly, on average, conired that adding the potential or assortative ating allowed populations to escape their stable itness inia at z 0 via speciation. The results o one such siulation are illustrated in Figure 4. The population was initialized with equal probabilities o 1 and 1 alleles at all ating loci so trait a is polyorphic with ean zero. The population initially evolves toward the itness peak corresponding to the ost abundant resource (z 0) and the directional selection changes to disruptive selection as the population approaches z 0. Assortative ating then evolves in a process analogous to reinorceent (Fig. 4C). This allows the population to split into two ecologically distinct species, as shown by the branching in both ales and eales (Fig. 4A, B). Note that because o strong assortative ating, the two eerging species are reproductively isolated. The increase in phenotypic variation resulting ro evolutionary branching equalizes the itness across dierent phenotypes, lattening the itness unction (Fig. 4F). SIMULTANEOUS MODEL OF DIMORPHISM AND SPECIATION Given that disruptive selection can result in either sexual diorphis or sypatric speciation, we now turn to the question o which outcoe is ore likely when considered siultaneously. Because both ors o divergence have identical ecological prerequisites ( c k ), we ocus our attention on the potentially iportant genetic paraeters o this odel: N shared /N total and s. The orer paraeter puts an upper bound

7 SEXUAL DIMORPHISM AND ADAPTIVE SPECIATION 439 FIG. 3. The probability that a eale ates with a ale is given by the ating unction, equation (1), and depends on the dierence in their ecological (or arker) phenotypes, and on the eale s degree o assortative ating, a. In addition, the paraeter s in equation (1) deterines the shape o the ate choice unction. Lower values o s steepen the surace and correspond to a higher genetic potential or assortative ating (A), whereas higher values o s latten the surace and correspond to a lower genetic potential or assortative ating (B). on the extent o phenotypic divergence between the sexes, and the latter deterines how ast ating becoes strongly assortative when the ating trait changes ro 0 to 1 or 1. We investigated the relative robustness o each evolutionary outcoe by actorially varying each paraeter: (N shared /N total 0, 0.1, 0.,...,1.0; s 0.0, 0.05, 0.03,...,0.1). This was done or a ixed ecological scenario. Our extensive nuerical siulations showed that all the results reported below hold qualitatively or any ecological scenario avoring divergence. For each cobination o the two paraeters N shared / N total and s we ran 10 replicate nuerical siulations. All siulations started with populations that were phenotypically variable with a ean o zero (equal probability or each allele at all ecological and ating loci) or the evolving characters and were run or 000 generations. Three ain observations eerge ro these siulations. First, speciation is inhibited in populations with a high capacity or sexual diorphis (Fig. 5A). Second, diorphis is inhibited in populations with a high capacity or assortative ating (Fig. 5B). Third, contrary to our initial expectations it is possible to siultaneously achieve diorphis and speciation (Fig. 5C). We discuss each o these conclusions in turn. It is not surprising that speciation was ost coon in the area o paraeter space with the highest potential assortative ating (s 0.04, Fig. 5A). However, the requency o speciation declines as the population s potential or sexual diorphis increases (lower values o N shared /N total, Fig. 5A), even when s is very sall. This inhibition could relect either a direct conlict between assortative ating and diorphis or an indirect eect ediated via the itness unction. As noted above, diorphis eliinates disruptive selection (Fig. 1E), so i diorphis is aster, it ay reove the ipetus or speciation. Additional siulations conired that diorphis tends to evolve ore quickly than speciation. We ran 50 replicate siulations or each o three genetic systes, noting the tie to diorphis or speciation in each run. When diorphis was the only possible result (N shared /N total 0, s 10), it evolved aster than the ean tie to speciation when speciation was the only possibility (N shared /N total 1, s 0.05; c. Fig. 6A and 6B). Siilarly, when the two processes were allowed to copete within a single siulation (N shared /N total 0.4, s 0.05), the ean tie to diorphis was uch shorter than the tie to speciation (c. Fig. 6C and 6D). This dierence relects the act that disruptive selection can act directly on ale and eale ecological traits, but only indirectly on the level o assortative ating. Although the potential or diorphis reduces the probability o speciation, the reverse is also true. When the potential or assortative ating was weak (s 0.1), diorphis evolved or all values o N shared /N total except N shared /N total 1 (Fig. 5B), where diorphis is ipossible. However, as the potential or assortative ating increased (lower values o the ating paraeter s), diorphis becae less coon, restricted to situations where the sexes were largely independent (N shared /N total 0.5). Speciation can inhibit sexual diorphis in several ways. First, because both processes rely on stochastic eects, speciation occasionally occurs beore, and thus preepts, sexual diorphis (16 o 50 siulations or Fig. 6C, D). Second, there is a undaental antagonis between positive assortative ating and a sexual diorphis: eales cannot siultaneously preer ates that are ost like theselves ecologically and still aintain an ecological sexual diorphis. I soe degree o positive assortative ating (but not ull speciation) evolves beore a sexual diorphis, this will liit the degree to which the sexes ay partition resources, because ecologically divergent ales will be eliinated by sexual selection.

8 440 D. I. BOLNICK AND M. DOEBELI FIG. 4. Siulation o speciation in response to resource copetition. Male (A) and eale (B) phenotype distributions initially evolve toward the ode o the resource distribution, ater which the level o assortative ating increases (C) and branching occurs in both sexes, indicating speciation. Darker shading indicates a greater nuber o individuals o a given phenotype at a given tie. Fitness unctions are shown or generation 10 (D), 100 (E), and 190 (F). Dashed vertical lines indicate the points in tie corresponding to each itness unction. The ean phenotypes or ales ( ) and eales () are arked on the itness unctions. Both sexes were initially onoorphic or the ecological trait z 1.0 and polyorphic or assortativeness with ean a 0. Paraeter values were: N shared / N total 1.0, s 0.05, K , k 1.0, c 0.5, r 5, 0.001, N total 10, N assort 5. The third liit to sexual diorphis depends heavily on N shared /N total. I the axiu distance between the sexes is genetically constrained to be less than the distance between the two stable phenotypic optia, equation (5), sexual diorphis will be insuicient to eliinate the disruptive selection. Diorphis ight then evolve teporarily (because it is aster than speciation), but be replaced by speciation, which can ore eectively equalize itness across phenotypes. An exaple o this sequential sexual diorphis and speciation is shown in Figure 7. A population initially centered on the resource optiu (z 0) is subject to disruptive selection (Fig. 7D) in period a (generations 0 to 90), ater which a slight diorphis evolves (period b). The degree o diorphis is liited by genetic constraints (N shared /N total 0.7). Because phenotypic divergence is liited, the itness unction does not latten greatly and the total population size

9 SEXUAL DIMORPHISM AND ADAPTIVE SPECIATION 441 reains low, though arginally higher than in period a (Fig. 7F). This sexual diorphis then collapses, returning to a period o interediate ecological phenotypes, disruptive selection, low population size, but increasing assortative ating (period c). When assortative ating is strong enough speciation occurs (period d). With the advent o speciation, the phenotype distributions o both sexes biurcate, assortative ating reains consistently high, disruptive selection ceases (Fig. 7E), and population sizes increase draatically (Fig. 7F). This last eect is particularly noteworthy because it indicates that the higher phenotypic variance has increased the overall carrying capacity o the population an eect that was not achieved by the genetically constrained sexual diorphis. So ar we have shown that speciation and ecological sexual diorphis are utually antagonistic. Diorphis can preept speciation, whereas assortative ating can restrict or soeties replace diorphis. It was thereore surprising to ind soe siulations that resulted in both sexual diorphis and speciation (Fig. 5C). In contrast to previous odels o adaptive speciation, in this case speciation entails strong negative, rather than positive, assortative ating. The ecological phenotype distributions o both sexes becoe biodal, with the two ale odes toward the phenotype extrees, and the eale odes closer to the interior (Fig. 8). Thus, each group o eales is urthest ro a dierent group o ales. Due to strong negative assortative ating, each group o eales ates with the ales ecologically least like the, rejecting the ore phenotypically siilar ales. Note that the existence o our phenotypic clusters in this scenario is a relection o the act the diorphic equilibriu (5) in the analytical odel is an evolutionary branching point: with negative assortative ating and concoitant speciation into two sexually diorphic species, a iner partitioning o niche space is possible than with sexual diorphis alone. However, this particular outcoe is rare because it requires a inely balanced set o paraeters. Assortative ating ust be strong enough to aintain two species, while N shared /N total ust be sall enough to allow diorphis yet not so sall that diorphis preepts speciation. Assortative Mating Based on Marker Phenotypes In this section we investigate to what extent the conlict between diorphis and speciation carries over to cases in which assortative ating is not based on traits under ecological selection, but instead on ecologically neutral arker traits, such as coloration. For speciation to occur in this situation, a linkage disequilibriu between the arker trait and the ecological trait ust develop, so that assortative ating can indirectly latch onto the ecological trait. Classically, recobination between the arker and the ecological trait is expected to severely ipede speciation with this type o as- FIG. 5. Shaded contour plots indicate requency o speciation (A), sexual diorphis (B), and cases o siultaneous diorphis and speciation (C) as a unction o the potential or assortative ating (s) and the genetic independence o the sexes (N shared /N total ). For each cobination o paraeter values, we ran 10 siulations or 000 generations. The proportion o runs resulting in a particular outcoe is indicated by the shading, ranging ro white (0%) to black (100%). Populations were initially polyorphic or both ecological and ating traits with eans o zero. K , k 1.0, c 0.5, r 5, 0.001, N total 10, N assort 5.

10 44 D. I. BOLNICK AND M. DOEBELI FIG. 6. Box plots o the tie to diorphis (dark boxes) or speciation (light boxes), showing quartiles (boxes), 95% conidence intervals (horizontal lines), and outliers (dots) or 50 replicates o each o three scenarios (A, B, and C/D). (A) Diorphis only, due to rando ating (s 10) and coplete independence between ale and eale ecological phenotypes (N shared /N total 0). (B) Speciation only, due to potentially strong assortative ating (s 0.05) and sexes are not independent (N shared /N total 1). Speciation (B) occurs an order o agnitude ore slowly than sexual diorphis (A), t , P When both speciation (C) and diorphis (D) are possible outcoes o a single siulation (s 0.05, N shared /N total 0.4), diorphis still occurs ore rapidly (t , P ), although 16 o 50 replicate siulations led to speciation irst and ailed to evolve a sexual diorphis. Paraeter values K , k 0.75, c 0.5, r 5, 0.001, N total 10, N assort 5, with 5000 generations per siulation. sortative ating (Felsenstein 1981). However, Dieckann and Doebeli (1999) have shown that this expectation is in act unwarranted, and that speciation can easily occur even in this scenario, albeit or slightly ore restrictive ecological paraeters than in the case where assortative ating is based on the ecological trait. Following Dieckann and Doebeli (1999), we incorporate arker-based assortative ating by assuing that there is a third set o N arker diallelic loci deterining an ecologically neutral trait that is expressed in both sexes. As beore, ating depends on assortability trait a, and ay be disassortative, rando, or assortative to varying degrees, but now ate choice, equation (1), is based not on siilarity in the ecological trait, but in the neutral arker trait. Thus, in Figure 3 the x-axis now represents the dierence in the value o the arker trait between two potential ating partners, which varies between N arker and N arker. It is assued that the arker loci reely recobine with all the other loci. In accordance with the results o Dieckann and Doebeli (1999), adaptive speciation occurs in our odels with arker-based assortative ating i N shared N total, and i the paraeter s scaling the assortative ating unction is low enough.. However, i N shared N total, a new type o evolutionary dynaics can be seen, during which the ancestral population splits into two sexually diorphic descendant species with positive assortative ating (Fig. 9). Two clusters o individuals exist at opposite ends o the arker trait axis, representing two reproductively isolated species with high assortativeness. Within each species ale and eale ecological traits are diorphic. Thus, assortative ating based on a arker trait can alleviate the antagonis between sexual diorphis and positive assortative ating: as long as the sexes have the sae arker trait (and hence ate with each other), they or a species even i they are ecologically dierentiated. Note again that sexual diorphis together with speciation due to arker-based assortative ating allows or iner niche partitioning than either sexual diorphis or speciation would i they occurred alone. Although ating based on a arker trait alleviates one o the sources o conlict between diorphis and speciation, the region o paraeter space in which speciation occurs is ore liited than seen or ating based on ecological traits. This is illustrated in Figure 10, or which we used the sae nuerical procedure as or Figure 5, except that single runs were continued or 5000 generations (to allow or the potentially slow process o linkage disequilibriu build-up). Even or low values o the scaling paraeter s, speciation will not occur when N shared /N total is uch less than one. Instead it appears that sexual diorphis is acilitated, as it is no longer countered by any positive assortative ating. Dieckann and Doebeli (1999) noted that the tie to speciation was uch longer when assortative ating was based on a arker trait than when based on the ecological traits, a result also seen in our siulations. Consequently sexual diorphis will alost always occur beore speciation in this case and eliinate or reduce the disruptive selection needed to drive speciation. The exception is when N shared /N total restricts the degree o diorphis, so that the sexes cannot diverge all the way to the ecologically deterined optia. Disruptive selection is then aintained until speciation occurs in addition to the diorphis, ore eectively equalizing copetition across phenotypes. DISCUSSION Although it is now widely accepted that adaptive speciation is both theoretically plausible (Turelli et al. 001; Dieckann et al. 003) and has been established epirically in at least a ew cases (Schliewen et al 1994, 001; Berlocher and Feder 00; Dres and Mallet 00), its generality reains contentious (Barraclough and Vogler 000; Coyne and Price 000). We thereore eel that it is useul to ove theoretical work away ro showing that adaptive speciation is possible to ore directly considering the conditions under which it is ore and less likely. For exaple, the odel by Dieckann and Doebeli (1999) highlighted the iportance o withinpopulation niche variation ( c k ) in generating requencydependent disruptive selection. This acilitates epirical study because inoration about the degree and requency o within-population variation (Bolnick et al. 00, 003) then tells us about the range o species likely to experience the ecologically ediated disruptive selection necessary or adaptive speciation. In this paper we have illustrated one way in which theory can shit ro considering easibility o adaptive speciation toward considering its expected requency o occurrence. Previous studies lead one to believe that speciation is likely

11 SEXUAL DIMORPHISM AND ADAPTIVE SPECIATION 443 FIG. 7. A siulation resulting in successive sexual diorphis and speciation. The ale (A) and eale (B) ecological phenotype distributions, and assortative ating distributions (C) are divided into our teporal regions, a, b, c, and d. These regions correspond to a: a period o disruptive selection (D), b: a period o weak sexual diorphis. Note that the ale distribution (A) is below the dark horizontal reerence line, whereas the eale distribution (B) is above the reerence line. Assortative ating becoes negative (C), because eales ust choose ales with phenotype traits dierent ro their own. The diorphis is weak due to genetic constraints. c: sexual diorphis is lost, d: speciation, indicated by biurcation o both sexes ecological traits (A, B), and high assortative ating (C). Following speciation (in period d), the itness unction is lattened (E), and population sizes increase due to reduced intraspeciic copetition (F). Populations were initially polyorphic or both ecological and ating traits with eans o zero. N shared /N total 0.7, s 0.05, K , k 0.75, c 0.5, r 5, 0.001, N total 10, N assort 5. whenever the necessary ecological conditions are ulilled (e.g., when c k ). In contrast, we have taken the view here that once disruptive selection has eerged ro the ecological interactions, it can have ore than one outcoe. Speciically, we have studied the relative likelihood with which disruptive selection leads to sexual diorphis or adaptive speciation. In doing so we have ound that the genetic basis o ale and eale ecological traits greatly aects whether a population will undergo speciation even when the ecological dynaics are suicient. Under the assuptions o our odel, a population with a large capacity or sexual diorphis is less likely to undergo speciation. Our siulations suggest two ain reasons why sexual diorphis and speciation are utually antagonistic outcoes o requency-dependent disruptive selection. First, there is a undaental conlict between sexual diorphis and a e-

12 444 D. I. BOLNICK AND M. DOEBELI FIG. 8. Siultaneous speciation and sexual diorphis in which assortative ating is based on ecological traits. A histogra o ale ecological traits (A) shows two ecological groups at z 1 and z 1. Feales (B) express both ecological and assortative ating traits, so their phenotype distribution is shown as a density plot (darker shading indicates ore individuals). Feales have split into two ecological groups, each with strong negative assortative ating. Straight lines connect conspeciic ales and eales, whereas phenotypically siilar ales and eales ail to ate due to negative assortative ating. N shared /N total 0., s 0.05, K , k 1.0, c 0.5, r 5, 0.001, N total 10, N assort 5. FIG. 9. Siultaneous speciation and sexual diorphis in which assortative ating is based on a neutral arker trait. Joint ecological and ating arker phenotype distributions are shown or ales (A) and eales (B). Due to strong positive assortative ating, ales and eales with high arker values (connected by a line) constitute one species, and ales and eales with low arker values (connected by a line) constitute a second species. Each o these species is ildly sexually diorphic. N shared /N total 0.4, s 0.05, K , k 1.0, c 0.5, r 5, 0.001, N total 10, N assort 5, N arker 5. ale s ability to choose a ate phenotypically like hersel. This conlict can be resolved i eales ate preerences are based on independent arker cues (e.g., color), rather than ecologically iportant diorphic traits. Alternatively, it is possible or speciation and diorphis to occur siultaneously when the speciation is based on negative assortative ating. Such dual diversiication is consistent with our analytical and siulation observation that each two-species or diorphic equilibriu is itsel a slight itness iniu (see Figs. 1E, 4F) and hence ay lead to still iner niche partitioning through successive speciation events. Our genetic siulations are too coarse to observe iner partitioning than the cobined speciation and diorphis. The second reason or the antagonis is indirect, ediated by changes in the shape o the itness unction. Both ecological sexual diorphis and adaptive speciation reduce or eliinate disruptive selection by equalizing the eect o copetition across phenotypes. Consequently, the outcoe that occurs irst will eliinate the selective orce that is needed to drive the alternative evolutionary outcoe. Our siulations consistently ound that sexual diorphis evolved aster than speciation, presuably because selection acts directly on the ecological traits but only indirectly on ating behavior. Only i diorphis is insuicient to eliinate disruptive selection, such as when the sexes cannot diverge enough to reach the ecologically deterined optia due to genetic con-

13 SEXUAL DIMORPHISM AND ADAPTIVE SPECIATION 445 FIG. 10. Shaded contour plots indicate requency o speciation (A), sexual diorphis (B), and siultaneous speciation and diorphis (C), when ate choice is based on an independent arker trait such as color, as a unction o the potential or assortative ating (s), and the genetic independence o the sexes (N shared /N total ). For each cobination o paraeter values, we ran 10 siulations or 5000 generations. The proportion o runs resulting in a particular outcoe is indicated by the shading, ranging ro white (0%) to black (100%). Populations were initially polyorphic or both ecological and ating traits with eans o zero. K , k 1.0, c 0.5, r 5, 0.001, N total 10, N assort 5, N arker 5. straints, can speciation ollow, either replacing or copleenting the diorphis. As with any theoretical odel, it is iportant to bear in ind the underlying assuptions and their consequences. In the context o this odel, soe noteworthy assuptions include the choice o particular ecological equations, the syetrical resource distributions and copetition unctions, constant individual niche widths ( c ), the absence o resource population dynaics or evolution, the schee or siulating genetic independence o ale and eale traits, and the lack o any cost o assortative ating or eales. Our results are robust to changes in any o these assuptions. For exaple, we chose one o a nuber o alternative ways to odel genetic divergence between sexes. Alternative schees could include loci that have opposite sex-dependent eects, speciically control diorphis, or arrest growth earlier in one sex than another. While our choice appears to be biologically reasonable based on QTL studies o diorphic traits (Mogil et al. 1997; Nuzhdin et al. 1997; Agulnik et al. 1998; Gurganus et al. 1999; Raos et al. 1999; Kopp et al. 003), the particular choice o genetic odel is not likely to be critical. Slatkin s (1984) odel o ecological sexual diorphis concluded that a sexual diorphis is possible whenever the genetic correlation between sexes is less than one, so dierent approaches to incorporate explicit genetics should yield equivalent results. Siilarly, adding a (sall) cost to assortative ating does not qualitatively change our results (D. I. Bolnick and M. Doebeli, unpubl. siulations). Also, asyetrical copetition has been shown to induce evolutionary branching (Kisdi and Geritz 1999; Doebeli and Dieckann 000), and hence the ecological preconditions or sexual diorphis as well. However, with asyetrical copetition the evolutionary branching point is not located at the resource axiu K 0, and the eerging phenotypic clusters have dierent population sizes, which ay have quantitative eects on the evolution o sexual diorphis because one sex will tend to be rarer than the other. Other assuptions ay prove to be ore critical to our results. For instance, i individual niche widths ( c ) were allowed to evolve, niche expansion ight occur ost quickly through increased within-phenotype niche width rather than increased between-phenotype variation (Taper and Case 1985). However, it is epirically quite reasonable to assue an upper liit on c relecting unctional or cognitive tradeos that ipose liits on individual niche breadth. Such trade-os are known to aintain individual specialization in a wide range o taxa (Bolnick et al. 003). Our results ight also be sensitive to reoving our assuption that the resource distribution neither evolves nor shows a nuerical response to predation. The addition o interspeciic copetitors would also greatly change the dynaics, as rare phenotypes that would otherwise have been avored by disruptive selection are subject to copetitive exclusion by other species. Finally, we have assued that the ecological traits whose evolution we study aect viability, but not ertility, o individuals. This assuption is in line with any previous theoretical studies, and it ultiately originates in the observation that the ertility r has no qualitative eect on the dynaics o two-species Lotka-Volterra copetition odels.

9. Sex Linkage and Other Sex Differences. Extensions to the HWC model to allow for differences between the sexes

9. Sex Linkage and Other Sex Differences. Extensions to the HWC model to allow for differences between the sexes 9. Sex Linkage and Other Sex Dierences Extensions to the HWC odel to allow or dierences between the sexes. Unequal allele requences or eales & ales: I, in the current generation, the two sexes have dierent

More information

Sexually Transmitted Diseases VMED 5180 September 27, 2016

Sexually Transmitted Diseases VMED 5180 September 27, 2016 Sexually Transitted Diseases VMED 518 Septeber 27, 216 Introduction Two sexually-transitted disease (STD) odels are presented below. The irst is a susceptibleinectious-susceptible (SIS) odel (Figure 1)

More information

A method to determine relative stroke detection efficiencies from multiplicity distributions

A method to determine relative stroke detection efficiencies from multiplicity distributions A ethod to deterine relative stroke detection eiciencies ro ultiplicity distributions Schulz W. and Cuins K. 2. Austrian Lightning Detection and Inoration Syste (ALDIS), Kahlenberger Str.2A, 90 Vienna,

More information

I. Understand get a conceptual grasp of the problem

I. Understand get a conceptual grasp of the problem MASSACHUSETTS INSTITUTE OF TECHNOLOGY Departent o Physics Physics 81T Fall Ter 4 Class Proble 1: Solution Proble 1 A car is driving at a constant but unknown velocity,, on a straightaway A otorcycle is

More information

Chapter 4 FORCES AND NEWTON S LAWS OF MOTION PREVIEW QUICK REFERENCE. Important Terms

Chapter 4 FORCES AND NEWTON S LAWS OF MOTION PREVIEW QUICK REFERENCE. Important Terms Chapter 4 FORCES AND NEWTON S LAWS OF MOTION PREVIEW Dynaics is the study o the causes o otion, in particular, orces. A orce is a push or a pull. We arrange our knowledge o orces into three laws orulated

More information

Bootstrapping Dependent Data

Bootstrapping Dependent Data Bootstrapping Dependent Data One of the key issues confronting bootstrap resapling approxiations is how to deal with dependent data. Consider a sequence fx t g n t= of dependent rando variables. Clearly

More information

Proc. of the IEEE/OES Seventh Working Conference on Current Measurement Technology UNCERTAINTIES IN SEASONDE CURRENT VELOCITIES

Proc. of the IEEE/OES Seventh Working Conference on Current Measurement Technology UNCERTAINTIES IN SEASONDE CURRENT VELOCITIES Proc. of the IEEE/OES Seventh Working Conference on Current Measureent Technology UNCERTAINTIES IN SEASONDE CURRENT VELOCITIES Belinda Lipa Codar Ocean Sensors 15 La Sandra Way, Portola Valley, CA 98 blipa@pogo.co

More information

Topic 5a Introduction to Curve Fitting & Linear Regression

Topic 5a Introduction to Curve Fitting & Linear Regression /7/08 Course Instructor Dr. Rayond C. Rup Oice: A 337 Phone: (95) 747 6958 E ail: rcrup@utep.edu opic 5a Introduction to Curve Fitting & Linear Regression EE 4386/530 Coputational ethods in EE Outline

More information

ma x = -bv x + F rod.

ma x = -bv x + F rod. Notes on Dynaical Systes Dynaics is the study of change. The priary ingredients of a dynaical syste are its state and its rule of change (also soeties called the dynaic). Dynaical systes can be continuous

More information

Optimization of Flywheel Weight using Genetic Algorithm

Optimization of Flywheel Weight using Genetic Algorithm IN: 78 7798 International Journal o cience, Engineering and Technology esearch (IJET) Volue, Issue, March 0 Optiization o Flywheel Weight using Genetic Algorith A. G. Appala Naidu*, B. T.N. Charyulu, C..C.V.aanaurthy

More information

In this chapter, we consider several graph-theoretic and probabilistic models

In this chapter, we consider several graph-theoretic and probabilistic models THREE ONE GRAPH-THEORETIC AND STATISTICAL MODELS 3.1 INTRODUCTION In this chapter, we consider several graph-theoretic and probabilistic odels for a social network, which we do under different assuptions

More information

Using EM To Estimate A Probablity Density With A Mixture Of Gaussians

Using EM To Estimate A Probablity Density With A Mixture Of Gaussians Using EM To Estiate A Probablity Density With A Mixture Of Gaussians Aaron A. D Souza adsouza@usc.edu Introduction The proble we are trying to address in this note is siple. Given a set of data points

More information

A NEW APPROACH TO DYNAMIC BUCKLING LOAD ESTIMATION FOR PLATE STRUCTURES

A NEW APPROACH TO DYNAMIC BUCKLING LOAD ESTIMATION FOR PLATE STRUCTURES Stability o Structures XIII-th Syposiu Zakopane 202 A NW APPROACH TO DYNAMIC BUCKLIN LOAD STIMATION FOR PLAT STRUCTURS T. KUBIAK, K. KOWAL-MICHALSKA Departent o Strength o Materials, Lodz University o

More information

A practical approach to real-time application of speaker recognition using wavelets and linear algebra

A practical approach to real-time application of speaker recognition using wavelets and linear algebra A practical approach to real-tie application o speaker recognition using wavelets and linear algebra Duc Son Pha, Michael C. Orr, Brian Lithgow and Robert Mahony Departent o Electrical and Coputer Systes

More information

A Simple Regression Problem

A Simple Regression Problem A Siple Regression Proble R. M. Castro March 23, 2 In this brief note a siple regression proble will be introduced, illustrating clearly the bias-variance tradeoff. Let Y i f(x i ) + W i, i,..., n, where

More information

The evolutionary dynamics of sexual dimorphism

The evolutionary dynamics of sexual dimorphism The evolutionary dynais o sexual diorphis To Van Dooren Institute o Biology Leiden Budapest 004 Whih type o ologial Polyorphis? Purple-throated Carib ulapis jugularis Helionia aribaea Helionia bihai Speies?

More information

General Properties of Radiation Detectors Supplements

General Properties of Radiation Detectors Supplements Phys. 649: Nuclear Techniques Physics Departent Yarouk University Chapter 4: General Properties of Radiation Detectors Suppleents Dr. Nidal M. Ershaidat Overview Phys. 649: Nuclear Techniques Physics Departent

More information

The economics of a stage-structured wildlife population model

The economics of a stage-structured wildlife population model The econoics o a stage-structured wildlie population odel Anders Skonhot and Jon Ola Olaussen Departent o Econoics Norwegian University o Science and Technology N-7491 Dragvoll-Trondhei, Norway Abstract

More information

Block failure in connections - including effets of eccentric loads

Block failure in connections - including effets of eccentric loads Downloaded ro orbit.dtu.dk on: Apr 04, 209 Block ailure in connections - including eets o eccentric loads Jönsson, Jeppe Published in: Proceedings o the 7th European conerence on steel and coposite structures

More information

Physically Based Modeling CS Notes Spring 1997 Particle Collision and Contact

Physically Based Modeling CS Notes Spring 1997 Particle Collision and Contact Physically Based Modeling CS 15-863 Notes Spring 1997 Particle Collision and Contact 1 Collisions with Springs Suppose we wanted to ipleent a particle siulator with a floor : a solid horizontal plane which

More information

The economics of a stage structured wildlife population model

The economics of a stage structured wildlife population model Stageodel115 The econoics o a stage structured wildlie population odel Anders Skonhot(*) and Jon Ola Olaussen Departent o Econoics Norwegian University o Science and Technology N-7491 Dragvoll-Trondhei,

More information

lecture 37: Linear Multistep Methods: Absolute Stability, Part I lecture 38: Linear Multistep Methods: Absolute Stability, Part II

lecture 37: Linear Multistep Methods: Absolute Stability, Part I lecture 38: Linear Multistep Methods: Absolute Stability, Part II lecture 37: Linear Multistep Methods: Absolute Stability, Part I lecture 3: Linear Multistep Methods: Absolute Stability, Part II 5.7 Linear ultistep ethods: absolute stability At this point, it ay well

More information

Genetic Drift and Polygenic Inheritance

Genetic Drift and Polygenic Inheritance Genetic Drift and Polygenic Inheritance FRANK B. LIVINGSTONE Depn rte n t of Anthropology, Uniuewi ty of Mic h igfiiz, A1 Arbor, Michigtrn 4814 KEY WORDS Siulation. Polygenic Inheritance. Optiizing Selection

More information

When Short Runs Beat Long Runs

When Short Runs Beat Long Runs When Short Runs Beat Long Runs Sean Luke George Mason University http://www.cs.gu.edu/ sean/ Abstract What will yield the best results: doing one run n generations long or doing runs n/ generations long

More information

2 Q 10. Likewise, in case of multiple particles, the corresponding density in 2 must be averaged over all

2 Q 10. Likewise, in case of multiple particles, the corresponding density in 2 must be averaged over all Lecture 6 Introduction to kinetic theory of plasa waves Introduction to kinetic theory So far we have been odeling plasa dynaics using fluid equations. The assuption has been that the pressure can be either

More information

Probability Distributions

Probability Distributions Probability Distributions In Chapter, we ephasized the central role played by probability theory in the solution of pattern recognition probles. We turn now to an exploration of soe particular exaples

More information

Figure 1: Equivalent electric (RC) circuit of a neurons membrane

Figure 1: Equivalent electric (RC) circuit of a neurons membrane Exercise: Leaky integrate and fire odel of neural spike generation This exercise investigates a siplified odel of how neurons spike in response to current inputs, one of the ost fundaental properties of

More information

Interactive Markov Models of Evolutionary Algorithms

Interactive Markov Models of Evolutionary Algorithms Cleveland State University EngagedScholarship@CSU Electrical Engineering & Coputer Science Faculty Publications Electrical Engineering & Coputer Science Departent 2015 Interactive Markov Models of Evolutionary

More information

A Low-Complexity Congestion Control and Scheduling Algorithm for Multihop Wireless Networks with Order-Optimal Per-Flow Delay

A Low-Complexity Congestion Control and Scheduling Algorithm for Multihop Wireless Networks with Order-Optimal Per-Flow Delay A Low-Coplexity Congestion Control and Scheduling Algorith for Multihop Wireless Networks with Order-Optial Per-Flow Delay Po-Kai Huang, Xiaojun Lin, and Chih-Chun Wang School of Electrical and Coputer

More information

PHY 171. Lecture 14. (February 16, 2012)

PHY 171. Lecture 14. (February 16, 2012) PHY 171 Lecture 14 (February 16, 212) In the last lecture, we looked at a quantitative connection between acroscopic and icroscopic quantities by deriving an expression for pressure based on the assuptions

More information

13.2 Fully Polynomial Randomized Approximation Scheme for Permanent of Random 0-1 Matrices

13.2 Fully Polynomial Randomized Approximation Scheme for Permanent of Random 0-1 Matrices CS71 Randoness & Coputation Spring 018 Instructor: Alistair Sinclair Lecture 13: February 7 Disclaier: These notes have not been subjected to the usual scrutiny accorded to foral publications. They ay

More information

Major questions of evolutionary genetics. Experimental tools of evolutionary genetics. Theoretical population genetics.

Major questions of evolutionary genetics. Experimental tools of evolutionary genetics. Theoretical population genetics. Evolutionary Genetics (for Encyclopedia of Biodiversity) Sergey Gavrilets Departments of Ecology and Evolutionary Biology and Mathematics, University of Tennessee, Knoxville, TN 37996-6 USA Evolutionary

More information

Course Notes for EE227C (Spring 2018): Convex Optimization and Approximation

Course Notes for EE227C (Spring 2018): Convex Optimization and Approximation Course Notes for EE227C (Spring 2018): Convex Optiization and Approxiation Instructor: Moritz Hardt Eail: hardt+ee227c@berkeley.edu Graduate Instructor: Max Sichowitz Eail: sichow+ee227c@berkeley.edu October

More information

A Better Algorithm For an Ancient Scheduling Problem. David R. Karger Steven J. Phillips Eric Torng. Department of Computer Science

A Better Algorithm For an Ancient Scheduling Problem. David R. Karger Steven J. Phillips Eric Torng. Department of Computer Science A Better Algorith For an Ancient Scheduling Proble David R. Karger Steven J. Phillips Eric Torng Departent of Coputer Science Stanford University Stanford, CA 9435-4 Abstract One of the oldest and siplest

More information

Equilibria on the Day-Ahead Electricity Market

Equilibria on the Day-Ahead Electricity Market Equilibria on the Day-Ahead Electricity Market Margarida Carvalho INESC Porto, Portugal Faculdade de Ciências, Universidade do Porto, Portugal argarida.carvalho@dcc.fc.up.pt João Pedro Pedroso INESC Porto,

More information

What is Probability? (again)

What is Probability? (again) INRODUCTION TO ROBBILITY Basic Concepts and Definitions n experient is any process that generates well-defined outcoes. Experient: Record an age Experient: Toss a die Experient: Record an opinion yes,

More information

Convergence of a Moran model to Eigen s quasispecies model

Convergence of a Moran model to Eigen s quasispecies model Convergence of a Moran odel to Eigen s quasispecies odel Joseba Dalau Université Paris Sud and ENS Paris June 6, 2018 arxiv:1404.2133v1 [q-bio.pe] 8 Apr 2014 Abstract We prove that a Moran odel converges

More information

This model assumes that the probability of a gap has size i is proportional to 1/i. i.e., i log m e. j=1. E[gap size] = i P r(i) = N f t.

This model assumes that the probability of a gap has size i is proportional to 1/i. i.e., i log m e. j=1. E[gap size] = i P r(i) = N f t. CS 493: Algoriths for Massive Data Sets Feb 2, 2002 Local Models, Bloo Filter Scribe: Qin Lv Local Models In global odels, every inverted file entry is copressed with the sae odel. This work wells when

More information

OBJECTIVES INTRODUCTION

OBJECTIVES INTRODUCTION M7 Chapter 3 Section 1 OBJECTIVES Suarize data using easures of central tendency, such as the ean, edian, ode, and idrange. Describe data using the easures of variation, such as the range, variance, and

More information

A Note on Scheduling Tall/Small Multiprocessor Tasks with Unit Processing Time to Minimize Maximum Tardiness

A Note on Scheduling Tall/Small Multiprocessor Tasks with Unit Processing Time to Minimize Maximum Tardiness A Note on Scheduling Tall/Sall Multiprocessor Tasks with Unit Processing Tie to Miniize Maxiu Tardiness Philippe Baptiste and Baruch Schieber IBM T.J. Watson Research Center P.O. Box 218, Yorktown Heights,

More information

Supporting information for Self-assembly of multicomponent structures in and out of equilibrium

Supporting information for Self-assembly of multicomponent structures in and out of equilibrium Supporting inforation for Self-assebly of ulticoponent structures in and out of equilibriu Stephen Whitela 1, Rebecca Schulan 2, Lester Hedges 1 1 Molecular Foundry, Lawrence Berkeley National Laboratory,

More information

Nonmonotonic Networks. a. IRST, I Povo (Trento) Italy, b. Univ. of Trento, Physics Dept., I Povo (Trento) Italy

Nonmonotonic Networks. a. IRST, I Povo (Trento) Italy, b. Univ. of Trento, Physics Dept., I Povo (Trento) Italy Storage Capacity and Dynaics of Nononotonic Networks Bruno Crespi a and Ignazio Lazzizzera b a. IRST, I-38050 Povo (Trento) Italy, b. Univ. of Trento, Physics Dept., I-38050 Povo (Trento) Italy INFN Gruppo

More information

Support Vector Machine Classification of Uncertain and Imbalanced data using Robust Optimization

Support Vector Machine Classification of Uncertain and Imbalanced data using Robust Optimization Recent Researches in Coputer Science Support Vector Machine Classification of Uncertain and Ibalanced data using Robust Optiization RAGHAV PAT, THEODORE B. TRAFALIS, KASH BARKER School of Industrial Engineering

More information

ANALYSIS OF HALL-EFFECT THRUSTERS AND ION ENGINES FOR EARTH-TO-MOON TRANSFER

ANALYSIS OF HALL-EFFECT THRUSTERS AND ION ENGINES FOR EARTH-TO-MOON TRANSFER IEPC 003-0034 ANALYSIS OF HALL-EFFECT THRUSTERS AND ION ENGINES FOR EARTH-TO-MOON TRANSFER A. Bober, M. Guelan Asher Space Research Institute, Technion-Israel Institute of Technology, 3000 Haifa, Israel

More information

Graphical Models in Local, Asymmetric Multi-Agent Markov Decision Processes

Graphical Models in Local, Asymmetric Multi-Agent Markov Decision Processes Graphical Models in Local, Asyetric Multi-Agent Markov Decision Processes Ditri Dolgov and Edund Durfee Departent of Electrical Engineering and Coputer Science University of Michigan Ann Arbor, MI 48109

More information

RAFIA(MBA) TUTOR S UPLOADED FILE Course STA301: Statistics and Probability Lecture No 1 to 5

RAFIA(MBA) TUTOR S UPLOADED FILE Course STA301: Statistics and Probability Lecture No 1 to 5 Course STA0: Statistics and Probability Lecture No to 5 Multiple Choice Questions:. Statistics deals with: a) Observations b) Aggregates of facts*** c) Individuals d) Isolated ites. A nuber of students

More information

Introduction to Machine Learning. Recitation 11

Introduction to Machine Learning. Recitation 11 Introduction to Machine Learning Lecturer: Regev Schweiger Recitation Fall Seester Scribe: Regev Schweiger. Kernel Ridge Regression We now take on the task of kernel-izing ridge regression. Let x,...,

More information

Now multiply the left-hand-side by ω and the right-hand side by dδ/dt (recall ω= dδ/dt) to get:

Now multiply the left-hand-side by ω and the right-hand side by dδ/dt (recall ω= dδ/dt) to get: Equal Area Criterion.0 Developent of equal area criterion As in previous notes, all powers are in per-unit. I want to show you the equal area criterion a little differently than the book does it. Let s

More information

Evolutionary branching and sympatric speciation. caused by different types of ecological interactions

Evolutionary branching and sympatric speciation. caused by different types of ecological interactions Doebeli and Dieckmann Evolutionary branching and sympatric speciation caused by different types of ecological interactions Michael Doebeli and Ulf Dieckmann Departments of Zoology and Mathematics University

More information

Kinematics and dynamics, a computational approach

Kinematics and dynamics, a computational approach Kineatics and dynaics, a coputational approach We begin the discussion of nuerical approaches to echanics with the definition for the velocity r r ( t t) r ( t) v( t) li li or r( t t) r( t) v( t) t for

More information

Inspection; structural health monitoring; reliability; Bayesian analysis; updating; decision analysis; value of information

Inspection; structural health monitoring; reliability; Bayesian analysis; updating; decision analysis; value of information Cite as: Straub D. (2014). Value of inforation analysis with structural reliability ethods. Structural Safety, 49: 75-86. Value of Inforation Analysis with Structural Reliability Methods Daniel Straub

More information

Feature Extraction Techniques

Feature Extraction Techniques Feature Extraction Techniques Unsupervised Learning II Feature Extraction Unsupervised ethods can also be used to find features which can be useful for categorization. There are unsupervised ethods that

More information

The E4ect of Evolution on Host}Parasitoid Systems

The E4ect of Evolution on Host}Parasitoid Systems J. theor. Biol. (2001) 209, 287}302 doi:10.1006/jtbi.2001.2263, available online at http://www.idealibrary.co on The E4ect of Evolution on Host}Parasitoid Systes RYUSUKE KON* AND YASUHIRO TAKEUCHI Departent

More information

Outperforming the Competition in Multi-Unit Sealed Bid Auctions

Outperforming the Competition in Multi-Unit Sealed Bid Auctions Outperforing the Copetition in Multi-Unit Sealed Bid Auctions ABSTRACT Ioannis A. Vetsikas School of Electronics and Coputer Science University of Southapton Southapton SO17 1BJ, UK iv@ecs.soton.ac.uk

More information

Chaotic Coupled Map Lattices

Chaotic Coupled Map Lattices Chaotic Coupled Map Lattices Author: Dustin Keys Advisors: Dr. Robert Indik, Dr. Kevin Lin 1 Introduction When a syste of chaotic aps is coupled in a way that allows the to share inforation about each

More information

Ocean 420 Physical Processes in the Ocean Project 1: Hydrostatic Balance, Advection and Diffusion Answers

Ocean 420 Physical Processes in the Ocean Project 1: Hydrostatic Balance, Advection and Diffusion Answers Ocean 40 Physical Processes in the Ocean Project 1: Hydrostatic Balance, Advection and Diffusion Answers 1. Hydrostatic Balance a) Set all of the levels on one of the coluns to the lowest possible density.

More information

Uncoupled automata and pure Nash equilibria

Uncoupled automata and pure Nash equilibria Int J Gae Theory (200) 39:483 502 DOI 0.007/s0082-00-0227-9 ORIGINAL PAPER Uncoupled autoata and pure Nash equilibria Yakov Babichenko Accepted: 2 February 200 / Published online: 20 March 200 Springer-Verlag

More information

An Approximate Model for the Theoretical Prediction of the Velocity Increase in the Intermediate Ballistics Period

An Approximate Model for the Theoretical Prediction of the Velocity Increase in the Intermediate Ballistics Period An Approxiate Model for the Theoretical Prediction of the Velocity... 77 Central European Journal of Energetic Materials, 205, 2(), 77-88 ISSN 2353-843 An Approxiate Model for the Theoretical Prediction

More information

5.1 The derivative or the gradient of a curve. Definition and finding the gradient from first principles

5.1 The derivative or the gradient of a curve. Definition and finding the gradient from first principles Capter 5: Dierentiation In tis capter, we will study: 51 e derivative or te gradient o a curve Deinition and inding te gradient ro irst principles 5 Forulas or derivatives 5 e equation o te tangent line

More information

Extension of CSRSM for the Parametric Study of the Face Stability of Pressurized Tunnels

Extension of CSRSM for the Parametric Study of the Face Stability of Pressurized Tunnels Extension of CSRSM for the Paraetric Study of the Face Stability of Pressurized Tunnels Guilhe Mollon 1, Daniel Dias 2, and Abdul-Haid Soubra 3, M.ASCE 1 LGCIE, INSA Lyon, Université de Lyon, Doaine scientifique

More information

16 Independence Definitions Potential Pitfall Alternative Formulation. mcs-ftl 2010/9/8 0:40 page 431 #437

16 Independence Definitions Potential Pitfall Alternative Formulation. mcs-ftl 2010/9/8 0:40 page 431 #437 cs-ftl 010/9/8 0:40 page 431 #437 16 Independence 16.1 efinitions Suppose that we flip two fair coins siultaneously on opposite sides of a roo. Intuitively, the way one coin lands does not affect the way

More information

Lecture #8-3 Oscillations, Simple Harmonic Motion

Lecture #8-3 Oscillations, Simple Harmonic Motion Lecture #8-3 Oscillations Siple Haronic Motion So far we have considered two basic types of otion: translation and rotation. But these are not the only two types of otion we can observe in every day life.

More information

Measures of average are called measures of central tendency and include the mean, median, mode, and midrange.

Measures of average are called measures of central tendency and include the mean, median, mode, and midrange. CHAPTER 3 Data Description Objectives Suarize data using easures of central tendency, such as the ean, edian, ode, and idrange. Describe data using the easures of variation, such as the range, variance,

More information

26 Impulse and Momentum

26 Impulse and Momentum 6 Ipulse and Moentu First, a Few More Words on Work and Energy, for Coparison Purposes Iagine a gigantic air hockey table with a whole bunch of pucks of various asses, none of which experiences any friction

More information

Polygonal Designs: Existence and Construction

Polygonal Designs: Existence and Construction Polygonal Designs: Existence and Construction John Hegean Departent of Matheatics, Stanford University, Stanford, CA 9405 Jeff Langford Departent of Matheatics, Drake University, Des Moines, IA 5011 G

More information

Block designs and statistics

Block designs and statistics Bloc designs and statistics Notes for Math 447 May 3, 2011 The ain paraeters of a bloc design are nuber of varieties v, bloc size, nuber of blocs b. A design is built on a set of v eleents. Each eleent

More information

Testing for Genetic Linkage in Families by a Variance-Components Approach in the Presence of Genomic Imprinting

Testing for Genetic Linkage in Families by a Variance-Components Approach in the Presence of Genomic Imprinting A. J. Hu. Genet. 70:75 757, 00 Report Testing or Genetic Linkage in Failies by a Variance-Coponents Approach in the Presence o Genoic Iprinting Sanjay Shete and Christopher I. Aos Departent o Epideiology,

More information

Easy Evaluation Method of Self-Compactability of Self-Compacting Concrete

Easy Evaluation Method of Self-Compactability of Self-Compacting Concrete Easy Evaluation Method of Self-Copactability of Self-Copacting Concrete Masanori Maruoka 1 Hiroi Fujiwara 2 Erika Ogura 3 Nobu Watanabe 4 T 11 ABSTRACT The use of self-copacting concrete (SCC) in construction

More information

Force and dynamics with a spring, analytic approach

Force and dynamics with a spring, analytic approach Force and dynaics with a spring, analytic approach It ay strie you as strange that the first force we will discuss will be that of a spring. It is not one of the four Universal forces and we don t use

More information

Evolutionary Branching and Sympatric Speciation Caused by Different Types of Ecological Interactions

Evolutionary Branching and Sympatric Speciation Caused by Different Types of Ecological Interactions vol. 156, supplement the american naturalist october 000 Evolutionary Branching and Sympatric Speciation Caused by Different Types of Ecological Interactions Michael Doebeli 1,* and Ulf Dieckmann, 1. Departments

More information

Functions: Review of Algebra and Trigonometry

Functions: Review of Algebra and Trigonometry Sec. and. Functions: Review o Algebra and Trigonoetry A. Functions and Relations DEFN Relation: A set o ordered pairs. (,y) (doain, range) DEFN Function: A correspondence ro one set (the doain) to anther

More information

Ph 20.3 Numerical Solution of Ordinary Differential Equations

Ph 20.3 Numerical Solution of Ordinary Differential Equations Ph 20.3 Nuerical Solution of Ordinary Differential Equations Due: Week 5 -v20170314- This Assignent So far, your assignents have tried to failiarize you with the hardware and software in the Physics Coputing

More information

Physics 4A Solutions to Chapter 15 Homework

Physics 4A Solutions to Chapter 15 Homework Physics 4A Solutions to Chapter 15 Hoework Chapter 15 Questions:, 8, 1 Exercises & Probles 6, 5, 31, 41, 59, 7, 73, 88, 90 Answers to Questions: Q 15- (a) toward -x (b) toward +x (c) between -x and 0 (d)

More information

The Transactional Nature of Quantum Information

The Transactional Nature of Quantum Information The Transactional Nature of Quantu Inforation Subhash Kak Departent of Coputer Science Oklahoa State University Stillwater, OK 7478 ABSTRACT Inforation, in its counications sense, is a transactional property.

More information

Analyzing Simulation Results

Analyzing Simulation Results Analyzing Siulation Results Dr. John Mellor-Cruey Departent of Coputer Science Rice University johnc@cs.rice.edu COMP 528 Lecture 20 31 March 2005 Topics for Today Model verification Model validation Transient

More information

Work, Energy and Momentum

Work, Energy and Momentum Work, Energy and Moentu Work: When a body oves a distance d along straight line, while acted on by a constant force of agnitude F in the sae direction as the otion, the work done by the force is tered

More information

Deflation of the I-O Series Some Technical Aspects. Giorgio Rampa University of Genoa April 2007

Deflation of the I-O Series Some Technical Aspects. Giorgio Rampa University of Genoa April 2007 Deflation of the I-O Series 1959-2. Soe Technical Aspects Giorgio Rapa University of Genoa g.rapa@unige.it April 27 1. Introduction The nuber of sectors is 42 for the period 1965-2 and 38 for the initial

More information

Extra-Pair Mating and Evolution of Cooperative Neighbourhoods

Extra-Pair Mating and Evolution of Cooperative Neighbourhoods Extra-Pair Mating and Evolution o Cooperative Neighbourhoods Sigrunn Eliassen *, Christian Jørgensen 2 Departent o Biology, University o Bergen, Bergen, Norway, 2 Uni Research, Bergen, Norway Abstract

More information

Sympatric Speciation

Sympatric Speciation Sympatric Speciation Summary Speciation mechanisms: allopatry x sympatry The model of Dieckmann & Doebeli Sex Charles Darwin 1809-1882 Alfred R. Wallace 1823-1913 Seleção Natural Evolution by natural selection

More information

Probability and Stochastic Processes: A Friendly Introduction for Electrical and Computer Engineers Roy D. Yates and David J.

Probability and Stochastic Processes: A Friendly Introduction for Electrical and Computer Engineers Roy D. Yates and David J. Probability and Stochastic Processes: A Friendly Introduction for Electrical and oputer Engineers Roy D. Yates and David J. Goodan Proble Solutions : Yates and Goodan,1..3 1.3.1 1.4.6 1.4.7 1.4.8 1..6

More information

Synchronization in large directed networks of coupled phase oscillators

Synchronization in large directed networks of coupled phase oscillators CHAOS 16, 015107 2005 Synchronization in large directed networks of coupled phase oscillators Juan G. Restrepo a Institute for Research in Electronics and Applied Physics, University of Maryland, College

More information

3.3 Variational Characterization of Singular Values

3.3 Variational Characterization of Singular Values 3.3. Variational Characterization of Singular Values 61 3.3 Variational Characterization of Singular Values Since the singular values are square roots of the eigenvalues of the Heritian atrices A A and

More information

ESTIMATING AND FORMING CONFIDENCE INTERVALS FOR EXTREMA OF RANDOM POLYNOMIALS. A Thesis. Presented to. The Faculty of the Department of Mathematics

ESTIMATING AND FORMING CONFIDENCE INTERVALS FOR EXTREMA OF RANDOM POLYNOMIALS. A Thesis. Presented to. The Faculty of the Department of Mathematics ESTIMATING AND FORMING CONFIDENCE INTERVALS FOR EXTREMA OF RANDOM POLYNOMIALS A Thesis Presented to The Faculty of the Departent of Matheatics San Jose State University In Partial Fulfillent of the Requireents

More information

The Wilson Model of Cortical Neurons Richard B. Wells

The Wilson Model of Cortical Neurons Richard B. Wells The Wilson Model of Cortical Neurons Richard B. Wells I. Refineents on the odgkin-uxley Model The years since odgkin s and uxley s pioneering work have produced a nuber of derivative odgkin-uxley-like

More information

USEFUL HINTS FOR SOLVING PHYSICS OLYMPIAD PROBLEMS. By: Ian Blokland, Augustana Campus, University of Alberta

USEFUL HINTS FOR SOLVING PHYSICS OLYMPIAD PROBLEMS. By: Ian Blokland, Augustana Campus, University of Alberta 1 USEFUL HINTS FOR SOLVING PHYSICS OLYMPIAD PROBLEMS By: Ian Bloland, Augustana Capus, University of Alberta For: Physics Olypiad Weeend, April 6, 008, UofA Introduction: Physicists often attept to solve

More information

The Weierstrass Approximation Theorem

The Weierstrass Approximation Theorem 36 The Weierstrass Approxiation Theore Recall that the fundaental idea underlying the construction of the real nubers is approxiation by the sipler rational nubers. Firstly, nubers are often deterined

More information

Sequence Analysis, WS 14/15, D. Huson & R. Neher (this part by D. Huson) February 5,

Sequence Analysis, WS 14/15, D. Huson & R. Neher (this part by D. Huson) February 5, Sequence Analysis, WS 14/15, D. Huson & R. Neher (this part by D. Huson) February 5, 2015 31 11 Motif Finding Sources for this section: Rouchka, 1997, A Brief Overview of Gibbs Sapling. J. Buhler, M. Topa:

More information

On Lotka-Volterra Evolution Law

On Lotka-Volterra Evolution Law Advanced Studies in Biology, Vol. 3, 0, no. 4, 6 67 On Lota-Volterra Evolution Law Farruh Muhaedov Faculty of Science, International Islaic University Malaysia P.O. Box, 4, 570, Kuantan, Pahang, Malaysia

More information

Upper bound on false alarm rate for landmine detection and classification using syntactic pattern recognition

Upper bound on false alarm rate for landmine detection and classification using syntactic pattern recognition Upper bound on false alar rate for landine detection and classification using syntactic pattern recognition Ahed O. Nasif, Brian L. Mark, Kenneth J. Hintz, and Nathalia Peixoto Dept. of Electrical and

More information

Research in Area of Longevity of Sylphon Scraies

Research in Area of Longevity of Sylphon Scraies IOP Conference Series: Earth and Environental Science PAPER OPEN ACCESS Research in Area of Longevity of Sylphon Scraies To cite this article: Natalia Y Golovina and Svetlana Y Krivosheeva 2018 IOP Conf.

More information

Adapting the Pheromone Evaporation Rate in Dynamic Routing Problems

Adapting the Pheromone Evaporation Rate in Dynamic Routing Problems Adapting the Pheroone Evaporation Rate in Dynaic Routing Probles Michalis Mavrovouniotis and Shengxiang Yang School of Coputer Science and Inforatics, De Montfort University The Gateway, Leicester LE1

More information

3D acoustic wave modeling with a time-space domain dispersion-relation-based Finite-difference scheme

3D acoustic wave modeling with a time-space domain dispersion-relation-based Finite-difference scheme P-8 3D acoustic wave odeling with a tie-space doain dispersion-relation-based Finite-difference schee Yang Liu * and rinal K. Sen State Key Laboratory of Petroleu Resource and Prospecting (China University

More information

SPECTRUM sensing is a core concept of cognitive radio

SPECTRUM sensing is a core concept of cognitive radio World Acadey of Science, Engineering and Technology International Journal of Electronics and Counication Engineering Vol:6, o:2, 202 Efficient Detection Using Sequential Probability Ratio Test in Mobile

More information

Lower Bounds for Quantized Matrix Completion

Lower Bounds for Quantized Matrix Completion Lower Bounds for Quantized Matrix Copletion Mary Wootters and Yaniv Plan Departent of Matheatics University of Michigan Ann Arbor, MI Eail: wootters, yplan}@uich.edu Mark A. Davenport School of Elec. &

More information

Estimating flow properties of porous media with a model for dynamic diffusion

Estimating flow properties of porous media with a model for dynamic diffusion Estiating low properties o porous edia with a odel or dynaic diusion Chuntang Xu*, Jerry M. Harris, and Youli Quan, Geophysics Departent, Stanord University Suary We present an approach or estiating eective

More information

The proofs of Theorem 1-3 are along the lines of Wied and Galeano (2013).

The proofs of Theorem 1-3 are along the lines of Wied and Galeano (2013). A Appendix: Proofs The proofs of Theore 1-3 are along the lines of Wied and Galeano (2013) Proof of Theore 1 Let D[d 1, d 2 ] be the space of càdlàg functions on the interval [d 1, d 2 ] equipped with

More information

7. Renormalization and universality in pionless EFT

7. Renormalization and universality in pionless EFT Renoralization and universality in pionless EFT (last revised: October 6, 04) 7 7. Renoralization and universality in pionless EFT Recall the scales of nuclear forces fro Section 5: Pionless EFT is applicable

More information

III.H Zeroth Order Hydrodynamics

III.H Zeroth Order Hydrodynamics III.H Zeroth Order Hydrodynaics As a first approxiation, we shall assue that in local equilibriu, the density f 1 at each point in space can be represented as in eq.iii.56, i.e. f 0 1 p, q, t = n q, t

More information

A DESIGN GUIDE OF DOUBLE-LAYER CELLULAR CLADDINGS FOR BLAST ALLEVIATION

A DESIGN GUIDE OF DOUBLE-LAYER CELLULAR CLADDINGS FOR BLAST ALLEVIATION International Journal of Aerospace and Lightweight Structures Vol. 3, No. 1 (2013) 109 133 c Research Publishing Services DOI: 10.3850/S201042862013000550 A DESIGN GUIDE OF DOUBLE-LAYER CELLULAR CLADDINGS

More information

Testing equality of variances for multiple univariate normal populations

Testing equality of variances for multiple univariate normal populations University of Wollongong Research Online Centre for Statistical & Survey Methodology Working Paper Series Faculty of Engineering and Inforation Sciences 0 esting equality of variances for ultiple univariate

More information