versión impresa ISSN 0716-078X
Rev. chil. hist. nat. v.83 n.4 Santiago dic. 2010
Revista Chilena de Historia Natural 83: 479-495, 2010
© Sociedad de Biología de Chile
SPECIAL FEATURE: DARWINIAN CORE AND POST-DARWINIAN EXTENSIONS
Is the evolutionary theory still useful? A review with examples
¿Es todavía útil la teoría evolutiva? Una revisión con ejemplos
ROBERTO F. NESPOLO
Instituto de Ecología y Evolución, Universidad Austral de Chile, Campus Isla Teja, Valdivia, Chile e-mail: firstname.lastname@example.org
Evolutionary biology is experiencing an exceptional process of revisión and outreach because of the 200-anniversary if the birth of Charles Darwin. As a consequence, the study of organic evolution and also its teaching are being discussed at several levels, by evolutionary biologists, biologists and scholars outside evolutionary biology and by the general public. In this scenario, a didactic explanation of how biologists address evolutionary research in real populations seems to be useful. Using actual research examples, here I tried to outline how the classic theory (termed here as the "basic scheme") is useful to answer relevant questions in biology and how a less dogmatic paradigm (or a more versatile one) would be needed when dealing with the most recent and extravagant cases of gene, genotype, phenotype and environment interactions. Specifically, I used three in-extenso examples of research driven by hypothesis-testing: (1) the changes in genetic architecture induced by sexuality in a cyclically parthenogenetic insect; (2) the test of the energetic definition of fitness through phenotypic selection studies; and (3) the assessment of the underlying causes of character displacement in Darwin finches. In the former two cases, it is argued that the basic scheme is useful and sufficient for testing relevant evolutionary hypotheses. In the third case, it is argued that something else is needed to explain the observed genetic variation that Geospiza species exhibit in Daphne major island (Galapagos). Finally, I outline some "extravagant" cases biological entities interacting, such as horizontal gene transfer, epigenetic inheritance, adaptive anticipatory conditioning, evolutionary capacitance and niche construction. This "post-modern" biology has been seriously proposed and demonstrated to be widespread in nature, which would justify an extended evolutionary synthesis.
Key words: character displacement, microevolution, modern synthesis, natural selection, population genetics.
La biología evolutiva está experimentando un inédito proceso de revisión y difusión debido al aniversario del natalicio de Charles Darwin. Como consecuencia, el estudio de la evolución orgánica y también su enseñanza están siendo discutidos a varios niveles, por biólogos evolutivos, biólogos y académicos fuera de la biología evolutiva, y por el público en general. En este escenario, una explicación didáctica de cómo los biólogos enfocan su investigación evolutiva en poblaciones reales podría ser útil. Usando ejemplos reales, he intentado presentar cómo la teoría clásica (definida como el "esquema básico") es útil para responder preguntas relevantes en biología y cómo un paradigma menos dogmático (o más versátil) podría ser necesario al tratar los casos más extravagantes de interacciones gene, genotipo, fenotipo y ambiente. Específicamente, he usado tres ejemplos in extenso de investigaciones guiadas por prueba de hipótesis: (1) los cambios en la arquitectura genética inducidos por sexualidad en un insecto partenogenético cíclico; (2) la puesta a prueba de la definición energética de la adecuación biológica a través de estudios de selección fenotípica; y (3) el estudio de las causas subyacentes al desplazamiento de caracteres en los pinzones de Darwin. En los dos primeros casos se argumenta que el esquema básico es útil y suficiente para probar hipótesis evolutivas relevantes. En el tercer caso se argumenta que algo más es necesario para explicar la variación genética observada en las especies de Geospiza que habitan en la isla Daphne mayor (Galapagos). Finalmente, se explican algunos casos "extravagantes" de interacción entre entidades biológicas, tales como transferencia horizontal de genes, herencia epigenética, condicionamiento anticipatorio adaptativo, capacitancia evolutiva y construcción del nicho. Esta biología "postmoderna" ha sido seriamente propuesta y de gran generalidad en la naturaleza, lo cual justificaría una síntesis evolutiva extendida.
Palabras clave: desplazamiento de caracteres, genética de poblaciones, microevolución, síntesis moderna, selección natural.
The 200-anniversary of Darwin birth has provoked the most vivid reactions both in the general public and within the academic community. In many academic circles (but not among evolutionary biologists) it has become common to hear some erroneous statements about modern evolutionary science. In fact, there exists some concern of specialized scholars in evolutionary research, about the common view that evolution is only natural selection, argued by people outside evolutionary biology, who adds that the discipline needs to be reconstructed from its principles. In fact, the evolutionary biologist Michael Lynch lucidly synthesized the opinion of many scholars regarding the year of Darwin and the need of an "extended" theory of evolution (see: Pigliucci 2007, Gowaty et al. 2008, Whitfield 2008):
"A lot has occurred during the last 150 years but the basic frame of evolutionary biology is rock solid. There not a single observation in the cell, molecular biology, or developmental biology that has provoked a significant change in our understanding of evolutionary principles. Of course, this does not means that molecular, cellular biologists, and developmental biologists are not needed to complete the understanding of the evolution process -they are needed most than ever- but to recognize that there are unsolved issues would be an ignorant mistake."
Thus, a not-so-technical explanation is in order. The evolutionary theory, also known as the modern synthesis, is one of the most successful scientific theories, but also one of the most complex. What we cali modern synthesis today is a body of knowledge developed by biologists after the Darwinism and new-Darwinism (Pigliucci 2007). There are a number of biological phenomena that are appropriately managed by the modern synthesis whereas there are a number of other processes that are not explained by this theory, especially those that have been discovered with modern technologies. Here, I will try to exemplify both, biological phenomena that are appropriately explained with the "basic scheme" of the modern synthesis, and also some phenomena that need some refinements.
The "classic" theory is not incorrect
What is commonly known as the modern synthesis, is the term generally applied to the fusión of neo-Darwinism, with the theoretical population genetics developed in great deal by J.B.S. Haldane, Sewal Wright and Ronald Fisher in the first part of the 1900 century (Haldane 1924, Fisher 1930, Wright 1931, Haldane 1932, Wright 1932, Wright 1943, Wright 1982, Gustafsson 1986, Wright 1988, Ewens 1989, Crow 1991, Wade & Goodnight 1991, Frank & Slatkin 1992, Price & Langen 1992, Edwards 1994, Coyne et al. 1997, Kirkpatrick & Barton 1997, Wade & Goodnight 1998, Leigh 1999, Coyne et al. 2000). This body of knowledge proposed the "language" by which phenotypes are read from genotypes, in the context of the change in alíele frequency of individuals in populations. Henee, this was a unidirectional premise, where phenotypes are the fixed ends of genotypes, which are re-organized after recombination in each (generally sexual) reproduction. Several advancements in ecological research, theoretical biology and molecular ecology were included in the modern synthesis late in the twentieth century, especially after the development and optimization of the polymerase chain reaction (PCR) procedure. This technique, together with the development of a great variety of genetic markers, provoked a revolution in population genetics and phylogeography, as many oíd theoretical models were now possible to be tested in actual populations. However, the recent advancement of genomics, developmental genetics and information technologies applied to the evolutionary science, has revealed a superbly varied picture of the reciprocal association between genes and phenotypes in organisms, populations and ecosystems. Still, it would be erroneous to indicate that this new insight negates in some way the original statements of the modern synthesis. In other words, genes are still important determinant of phenotypes; recombination, drift, population size and gene flow are still basic forces behind the observed gene-frequencies; and natural selection has never been seriously questioned as the most important mechanism behind the appearance of adaptations (Seeley 1986, Sinervo et al. 1992, Laland et al. 1999, Filchak et al. 2000, Higgie et al. 2000, Sinervo et al. 2000, Rice & Chippindale 2001, Abzhanov et al. 2004, Abzhanov et al. 2006, Seehausen et al. 2008, Harmon et al. 2009). Henee, what is probably under way is, according to Pigliucci (2007) an extended evolutionary synthesis rather than a replacement. Since this need is appropriately presented by this and other authors, here I explain some cases that I believe exemplify the basic scheme of the modern synthesis.
THE BASIC SCHEME: THE POPULATION/ QUANTITATIVE GENETICS MODEL
Imagine an individual plant or an animal, in which we measure two metric traits that we can graphically depict as in Fig. 1A. Now suppose that those phenotypic measurement are somewhat weighed by the degree by this particular trait is under genetic influence. This can only be conceived assuming that the trait is determined by many genes of small effect (Le., polygenic inheritance). Also, we are supposing the absence of any kind of interaction between genes (e.g., epistasis, dominance) and that the population is reasonably large to avoid the effects of genetic drift. Whatever the scale of this new variable is, this would be a magnitude that depends on both, the phenotypic value and how much heritable is the trait. This weighed attribute is commonly known as the breeding value, and a sample of such breeding values from a population would look as in Fig. 1B (Arnold et al. 2008). Now suppose that we are talking about two negatively correlated traits, such as clutch size and offspring size, and we represent the whole breeding values of the whole population, as in Fig. 1C. If we were considering just traits (not breeding values), Fig. 1C would be known as a negative phenotypic correlation. However, we are talking about a bivariate distribution of breeding values which shows a negative correlation, which is also known as the genetic correlation (Cheverud et al. 1983, Houle 1991). The variance of breeding values in each axis is also known as the genetic variance, which is usually summarized as heritability: the ratio between genetic variance and phenotypic variance (Houle 1992). Now imagine an adaptive landscape (Fig. 1D): some combinations of traits (here in dark) maximizes survival and reproduction (= fitness), and others minimize it (white) leading to "maladaptive" zones (also known as fitness valleys, in analogy of a contour landscape) (Wright 1932, Wright 1988, Arnold et al. 2008). If we over-impose our whole population of breeding values and the adaptive landscape (Fig. 1E), we would be witnessing an imminent outcome: an evolutionary change by natural selection (Fig. 1F). This representation shows directional natural selection acting on one trait but the distribution of breeding values (Le., the negative genetic correlation) provoked a change in the mean phenotype of both traits. But not only there was a change in the mean, but also in the variance of both trait, which was reduced. More striking, the original genetic correlation disappeared after this selective event. The representation of Fig. 1 is a cartoon of what is supposed to happen (under the basic scheme) during the origin of adaptations: a drastic reduction of genetic variance because of the fixation of alíeles in the population and a reduction of the potential for response to selection. However, it is possible that other processes, such as recombination, gene flow, and mutation increases genetic variation, compensating it reduction by selection, and contributing to its maintenance. The structure of genetic variances and covariances, it analytical treatment and statistical procedures aimed to compare and estimate them are the aims of comparative quantitative genetics (Arnold 1983, Steppan et al. 2002, Arnold et al. 2008).
Fig. 1: A graphic simulation of the distribution of breeding values in a population, two traits and an adaptive landscape. A: a single individual with breeding value y for trait Z1 and breeding value x for trait Z2. Breeding values could be considered phenotypic values weighed by how much heritable is the trait. B: fourteen individuals in the same population, with evident variation in their breeding values for both traits. C: the distribution of breeding values in the whole population, showing a negative genetic correlation between Z1 and Z2, and their means. This is what is known as an "evolutionary trade-off". D: an adaptive landscape, where fitness peaks (red) and valleys (blue) are shown for different traits combinations. E: the distribution of the breeding values over-imposed on the adaptive landscape showing that a proportion of individuals falling in the fitness valley (which would have minimum fitness) and other fraction falling in the fitness peak (which would have máximum fitness). F: the consequence of selection, within one generation (Le., without reproduc-tion), where the means Z1 and Z2 change to Z1' and Z2'. Three key consequences should be noted: (1) the change in the mean phenotype could be interpreted as natural selection on trait Z1 but as a consequence of the genetic correlation, trait Z2 is also affected; (2) a drastic reduction in genetic variance occurred, which limits future adaptive changes (and producing an adaptation when all the alíeles become fixed) and (3) that the genetic correlation disappeared.
Simulación gráfica de la distribución de los valores de cría en una población, dos rasgos y un paisaje adaptativo. A: un individuo con valores de cría y para el rasgo Z1 y valor de cría x para el rasgo Z2. Los valores de cría pueden ser considerados valores fenotípicos ponderados por el grado de control genético que ellos poseen. B: catorce individuos de la misma población, mostrando variación en sus valores de cría para ambos rasgos. C: la distribución de los valores de cría en la población completa, mostrando las medias y una correlación genética negativa entre Z1 y Z2. Esto es lo que se conoce como un "compromiso evolutivo". D: un paisaje adaptativo, donde los picos (rojo) y valles (azul) de adecuación se muestran para diferentes combinaciones de rasgos. E: la distribución de los valores de cría sobrepuesta en el paisaje adaptativo, mostrando una proporción de los individuos cayendo en el valle de adecuación (los cuales tendrán adecuación mínima) y otra proporción cayendo en el pico de adecuación (los cuales tendrán adecuación máxima). F: la consecuencia de la selección, dentro de una generación (Le., sin reproducción), donde las media Z1 y Z2 cambian a Z1' y Z2'. Tres consecuencias clave deben notarse: (1) el cambio en la media fenotípica se puede interpretar como selección natural en el rasgo Z1 pero como consecuencia de la correlación genética, el rasgo Z2 también cambia (se reduce su media); (2) una reducción drástica de la varianza genética, lo cual limita futuros cambios adaptativos (y produciendo una adaptación cuando todos los alelos se fijen por selección) y (3) que la correlación genética desapareció.
USING THE BASIC SCHEME I: STUDYING THE EFFECT OF SEXUALITY ON GENETIC ARCHITECTURE
There are many examples and case studies showing how the structure of genetic variances and covariances (also known as the "G" matrix) encapsulates the potentials and restrictions for adaptive evolution (Caswell & Sinauer 1989, McDonald et al. 1993, Roff 2000, Begin & Roff 2001, Phillips et al. 2001, Steppan et al. 2002, Begin & Roff 2003, Jones et al. 2003, Begin et al. 2004, Cano et al. 2004, Bochdansky et al. 2005b, Revell 2007, Arnold et al. 2008, Ovaskainen et al. 2008). Here I provide as example, our results in the clonal aphid Rhopalosiphum padi and the effect of sexuality on it (Nespolo et al. 2008, 2009). Aphids are cyclic parthenogenetic organisms that reproduce continuously by parthenogenesis, but reduction in temperature and photoperiod can provoke episodes of sexual reproduction. Clonal animalss and plants have the advantage that individuals can be replicated in a pedigree, being the clonal means of the trait, analogous to breeding values. This fact simplifies considerably the study of genetic (co) variances, since several individuals in a sample from an aphid population could be clones among them. Taking advantage of microsatellite markers and PCR, it is possible to sample individuals from nature and to determine how many clones are in a given population. After that, individuals can be asexually reproduced in the laboratory in order to obtain "living replicates" for a given clone and their traits can be measured. Then, genetic variance would be the variance of clonal means and genetic correlation would be its correlation (between two traits). Among other interesting features of aphids, different morphs (Le., sexual and asexual) can be induced in replicates of the same genotype, under specific environmental conditions. We used this system, considering the possibility to manipúlate sexual reproduction as a fixed treatment, to address the question of how much differences in the genetic architecture are expressed by different reproductive modes (see the complete study in Nespolo et al. 2009). Life history theory indicates that traits such as age at maturity and fecundity are fitness components, which in some insects can be modulated by the capacity of dispersión by producing winged individuals (Roff & Fairbairn 2007). This is the case of many species of aphids, where winged individuals are produced after a number of environmental and genetic determinants (Dixon & Kindlmann 1999). Thus we chose those traits in order to test whether evolutionary trade-offs are present, in the form of negative genetic correlations among those traits (Fig. 2), and whether they change in response to sexuality. To accomplish this, we sampled a population of aphids and identified 23 different genotypes by PCR amplification and using seven microsatellite loci, and we further reproduced them asexually during several generations. Then, also by asexual reproduction, we produced two set of replicates that were submitted to two treatments: sexual and asexual induction (for details see Nespolo et al. 2009). Interestingly, during the asexual phase we found important evolutionary trade-offs between fecundity, age at maturity and production of winged individuals (Fig. 2). But (in the same genotypes) these trade-offs disappeared during sexual reproduction, possibly because of a re-allocation energy pattern due to the expensive sexual forms. Recalling the adaptive landscape and distribution of breeding values depicted in Fig. 1, the presence of a fitness optimum at the upper-left area of the graph (Le., high dispersión capacity, high age at maturity and low fecundity in Fig. 2; a general reaction to crowding in insects) would produce, based on our results, an evolutionary shift towards reducing fecundity, delaying maturity and increasing the production of winged individuals during the asexual phase (Fig. 2B and 2D). However, this is not predicted to occur during sexuality, given the radically different distribution of clonal means (Fig. 2C and 2C). This is an example of the application of the basic scheme with little deviations from the modern synthesis. Perhaps the use of PCR amplification, microsatellite markers and clonal design could be considered as later advancements, but the rationale and the predictions are just as in Fig. 1. However, these results, which test the constancy of the G-matrix in response to reproductive mode, were considered novel and useful without needs to invoke any new paradigm.
Fig. 2: The potentials and restrictions to evolution in life histories of a cyclic parthenogenetic aphid (Rhopalo-siphum padi), as analyzed by comparative quantitative genetics. In this case, breeding values (each datapo-int) are represented by clonal means (± SE; N = 8-12 measured individuals per clone), and genetic correlations (tq ± SE of the estimate) are the Pearson product-moment correlation of clonal means between traits. This population alternates continuous parthenogenetic reproduction with episodes of sexual reproduction, a study case where the same population and even the same genotypes express radically different genetic architectu-re, which in turn predict different evolutionary trajectories. This is an example of fluctuating trade-offs in classic life-history traits: age at maturity and fecundity (lower panel) and specific life histories such as the production of winged and apterous individuals (upper panel). It can be seen that fairly high negative genetic correlations (constraints for adaptive evolution) are present during the asexual phase (B and D) but disap-pear during the sexual reproduction (A and C) (see details in Nespolo et al. 2009).
La potencialidad y restricciones a la evolución de historias de vida en un áfido partenogenético cíclico (Rhophalosiphum padt), analizada desde la perspectiva de la genética cuantitativa comparada. En este caso, los valores de cría (cada punto) están representados por las medias clónales (± EE; N = 8-12 individuos medidos por clon), y las correlaciones genéticas (rG ± EE del estimador) son las correlaciones de producto-momento de Pearson de las medias clónales entre rasgos. Esta población alterna reproducción parteno gen ética continua con episodios de reproducción sexual, un caso de estudio donde la misma población e incluso el mismo genotipo expresa arquitecturas genéticas radicalmente diferentes, lo cual a su vez predice trayectorias evolutivas diferentes. Este es un ejemplo de compromiso fluctuante en rasgos de historia de vida clásicos: edad de la madurez y fecundidad (abajo) y rasgos de historia de vida específicos como la producción de individuos alados o ápteros (arriba). Se puede ver que correlaciones genéticas altas y negativas (restricciones a la evolución adaptativa) están presentes durante la fase asexual (B y D) pero desaparecen durante la reproducción sexual (A y C) (véase detalles en Nespolo et al. 2009).
USING THE BASIC SCHEME II: VALIDATING THE ENERGETIC DEFINITION OF FITNESS
Natural selection is perhaps the most commonly known proposition of Darwin, and no other mechanism has been seriously proposed to explain the origin of adaptations. In fact, the oldest and also the most recent studies addressing the origin of adaptations gives to natural selection a central role (Williams 1966, Gadgil & Bossert 1970, O'Donald 1973, Boag & Grant 1981, Morris 1985, Endler 1986, Schluter & Smith 1986, Seeley 1986, Mousseau & Roff 1987, Fox 2000, Gubitz et al. 2000, Higgie et al. 2000, Kentner & Mesler 2000, Kohn et al. 2000, Szekely et al. 2000, Conner 2001, Kirk et al. 2001, Merila et al. 2001b, Rice & Chippindale 2001, Hey & Kliman 2002, Parsonage & Hughes 2002, Sheldon et al. 2003, Sinervo & Calsbeek 2003, Abzhanov et al. 2004, Cano et al. 2004, Ceplitis & Bengtsson 2004, Brommer et al. 2005, Abzhanov et al. 2006, Saldana et al. 2007, Anisimova & Liberles 2008).
The study of contemporary natural selection in wild populations, also known as "phenotypic selection studies" took its form after the theoretical framework introduced by Robertson and Price (Robertson 1966, Price 1970), who demonstrated that directional selection is equivalent with the covariance of fitness and the trait of interest. This approach was later applied to real data and non-linear fitness surfaces, and also to other forms of selection (Arnold 1983, Arnold & Wade 1984, Brodie et al. 1995). A great number of natural selection studies have been performed since then, which suggest that natural selection is strong, can fluctuate in sign, form and magnitude, and is widespread in all kind of organisms. Another conclusión of these studies was that almost every possible attribute of animalss and plants can be target of natural selection, depending on its impact on fitness (Primack & Kang 1989, Wiggins 1991, Linden 1992, Sorci & Clobert 1999, Barbraud 2000, Svensson & Sinervo 2000, Hoekstra et al. 2001, Kingsolver et al. 2001, Kirk et al. 2001, Kruuk et al. 2001, Medel 2001, Kruuk et al. 2003). However, the great majority of those studies were performed on morphological traits.
Physiological ecologists, during a long time worked making an important assumption regarding organisms in populations: that plants and animalss optimize the use of energy in order to maximize fitness. This was formerly known as the allocation principle, but later was renamed as the energetic definition of fitness (Cody 1966, Gadgil & Bossert 1970, Sibly & Calow 1986, Brown et al. 1993), and suppose that available energy is limiting in ecosystems, and organism need to allocate it to either biological functions (e.g., growth, reproduction, maintenance, movement). Henee, an important prediction of the hypothesis is that natural selection will promote those genotypes that optimize energy use. In other words, individuals that minimize the cost of living (i.e., maintenance metabolism in the case of animalss) would be promoted by selection since the surplus energy will maximize survival and fecundity (i.e., increasing fitness). To test this hypothesis, natural or phenotypic selection on (maintenance) energy consumption needs to be measured.
The problem to study natural selection in animalss relies on the fact that it is critical to mark, measure and recapture a great number of individuals. The obvious limitations of measuring energy metabolism in many individuals (which in most cases need to be measured in the lab) worsen the picture and have made these kinds of studies, prohibitive. Few indirect evidences suggesting that animalss optimize their energy budget by reducing maintenance costs, carne from ectotherms such as fish (Bochdansky et al. 2005) and terrestrial snails (Czarnoleski et al. 2008). The only direct attempts of testing the hypothesis through phenotypic selection studies, were done in endotherms (wild rodents) (Hayes & O'Connor 1999, Jackson et al. 2001, Boratynski & Koteja 2009). However, none of them yielded conclusive results. With this idea in mind, we took the challenge of testing the energetic definition of fitness in animalss, choosing the common terrestrial snail (Helix aspersa) as model. We chose this model because one of the problems of phenotypic selection analyses is related with the inherent low statistical power of the technique. This is a consequence of the uncertainty of assuming non-recaptured animalss as died animalss (when the fitness is measured as survival, which is the majority of the cases, e.g., Janzen 1993, Kruuk et al. 2000, Merila et al. 2001a, McAdam & Boutin 2003, Reale et al. 2003). By using an animal which does not move much (and henee, it is easily found), and more important, the deads are readily identified by the tagged empty shells, we obtained enough statistical power using a couple of hundreds snails. After capturing those individuals, we took them to the laboratory and we measured Standard Metabolic Rate at the routine temperature for snails (see Artacho & Nespolo 2009). We also characterized them morphologically in order to discard correlational selection with other traits. The final results of the survival analysis are presented in Fig. 3 (Artacho & Nespolo 2009). This "fitness profile" shows that selection promoted individuals with low-to-medium energy metabolism. In other words, natural selection seemed to act against "wasteful" individuals.
Fig. 3: Natural selection acting against high standard energy metabolism in the terrestrial snail Helix aspersa. A study showing that a physiological trait could be target of directional natural selection, in this case supporting the energetic definition of fitness which suggests that natural selection would promote energy optimization. This "fitness profile" shows a dichotomous fitness value (survival; 0 = dead; 1 = survived) in function of the trait value (standardized values to mean = zero and SD = 1), adjusted with a cubic-spline (non-parametric) proce-dure and 95 % confidence interval computed by bootstrap. As the fitness profile suggest, there was a combination of negative directional and stabilizing selection, as the linear (β) and non-linear (γ) selection gradients confirmed (* = P < 0.05; ** = P < 0.01; *** = P < 0.001). See details in Artacho & Nespolo (2009).
Selección natural actuando en contra de alto metabolismo estándar en el caracol terrestre Helix aspersa. Un estudio mostrando que un rasgo fisiológico puede ser blanco de la selección natural, en este caso apoyando la definición energética de la adecuación biológica, la cual sugiere que la selección natural promovería la optimización de la energía. Este "perfil de adecuación" muestra valores de adecuación dicotómicos (sobreviviencia; 0 = muerto; 1 = sobrevive) en función del valor del rasgo (valores estandarizados para media = 0 y SD = 1), ajustados mediante un procedimiento de spline cúbico (no paramétrico) e intervalos de confianza del 95 % calculados mediante bootstrap. Como el perfil de adecuación sugiere, existió una combinación de selección direccional negativa y estabili-zadora, tal como los gradientes de selección lineal (β) y no lineal (γ) confirmaron (* = P < 0.05; ** = P < 0.01; *** = P < 0.001). Véase detalles en Artacho & Nespolo (2009).
In terms of the basic scheme in Fig. 1, the snails study would be the kind of evidence needed for drawing the actual fitness landscape (related with the physiological phenotype, in this case). Of course, it has obvious limitations such as the fact that we were using trait-values and not breeding values, and the fact that the proxy of fitness is just survival (assuming that fecundity is constant). Still, these results were considered useful, since they summarize one of the few empirical supports to the energetic definition of fitness. These results were obtained exclusively using the basic scheme (fitness, genetic variances and covariances, see Fig. 1), as in measuring the effects of sexuality on aphids genetic architecture (Fig. 2).
USING THE BASIC SCHEME III (AND BEYOND): DARWIN FINCHES
One of the most classic examples of adaptive radiation and character displacement are the great variety of beak sizes and shapes, of Darwin finches, endemic to Galapagos Islands (Grant & Grant 2002, Grant 2003, Grant & Grant 2003). Among them, six species belong to the genus Geospiza (ground finches) and exhibit a continuous gradient in beak size and shapes, which matches closely the main food they usually consume. Henee, one extreme could be represented by the large ground finch (Geospiza magnirostris) which consumes big, hard seeds and uses its strong, short beak to crack their hard shells. The other extreme would be the cactus finch (Geospiza scandens), which use their small, long and pointed beak to feed almost exclusively on the pollen and nectar obtained from the flowers of cactuses. In the middle, a myriad of beak sizes and shapes are diversely related to their ecological (trophic) niche, exhibiting variation even at the population level (Grant & Grant 2002, Grant 2003, Grant & Grant 2003). From generalists to extreme specialists, the species of Darwin finches are distributed in the Galapagos archipelago as unique textbook examples showing sometimes striking niche separation when sympatric, and niche overlap when allopatric (Grant et al. 2000, Grant & Grant 2006).
Given the natural laboratory for studying evolutionary processes that they are, a number of evolutionary biologists did their careers studying Darwin finches in Galapagos, especially in Daphne Major Island, most of them inspired, or associated with Rosmary and Peter Grant (Weiner 2002). These researchers applied the whole battery of procedures based on ecological theory and the modern synthesis, including quantitative genetics (Boag & Grant 1978, Grant & Grant 2000b, Keller et al. 2001), population genetics (Grant et al. 2000, Keller et al. 2001), niche theory (Grant et al. 2000) and phenotypic selection studies (Boag & Grant 1981, Gibbs & Grant 1987, Grant & Grant 2000) to understand the processes behind the adaptive radiation that they observed , mostly in beak shape and body size, but also in song variation (Grant et al. 2000). This evidence suggests that directional selection was strong on beak morphology, but oscillating in sign (Fig. 4). In fact, the same directional selection gradient that we measured for the snails (see Fig. 3), but during 18 years in G. fortis and G. scandens indicate a highly fluctuating pattern of selection (Fig. 4, Grant & Grant 2002). Considerable amount of additive genetic variation in beak size and shape, and in body size provoked rapid responses to selection to opposite sides, depending on how dry or rainy were the years. This fact surely maintained the genetic variance in those traits, but several other factors, revealed with alozyme, microsatellite and mitochondrial DNA markers indicated large effective population sizes, introgression and hybridization which should have contributed to the maintenance or increase in genetic variation (Grant & Grant 1994, Grant & Grant 1996, Sato et al. 1999, Keller et al. 2001). Then, Darwin finches appeared to be living examples of the basic scheme (Fig. 1): additive genetic variation (i.e., the variance in breeding values for beak shape and body size) was high, and classic population genetic factors were demonstrated to be maintaining it. However, now the adaptive landscape was not static, changing dark zones (i.e., fitness peaks) into white (i.e., fitness valleys) depending on environmental conditions each year (see Fig. 1).
Fig. 4: Long term dataset of Grant & Grant (2002) experiment in two species of Darwin finches in Galapagos Islands. Each bar represents the magnitu-de of the directional selection gradient, showing how fluctuating could be natural selection across time, depending on environmental conditions. During dry years, positive selection (i.e., promoting big beaks) was the strongest (modified from Grant & Grant 2002). The authors also found a similar fluctuating pattern of selection in beak shape and body size (* = P < 0.05; ** = P < 0.01; *** = P < 0.005; **** = P< 0.001).
Experimento de largo plazo, de Grant & Grant (2002), en dos especies de pinzones de Darwin en las islas Galapagos. Cada barra representa la magnitud del gradiente de selección lineal () sobre el tamaño del pico, mostrando cuan fluctuante puede ser la selección en el tiempo, dependiendo de las condiciones ambientales. Durante los años secos, la selección positiva (i.e., promoviendo picos grandes) fue máxima (modificado de Grant & Grant 2002). Los autores encontraron un patrón similar en la forma del pico y el tamaño corporal (* = P < 0.05; ** = P < 0.01; *** = P < 0.005; **** = P<0.001).
It turned out, however, that the expression of the beak morphology was not under the effects of many genes of small effect, as would be the logic of "breeding values" (and the basic scheme). After a number of elegant experiments on Geospiza embryos, and through a combination of gene-expression patterns using microarray technology, Abzhanov and collaborators showed how the tridimensional structure of the beak in Darwin finches is determined by two gene-expression factors (Abzhanov et al. 2004, Abzhanov et al. 2006). In fact, in the chicken a zone of cell proliferation in the frontonasal mass is associated with the bone morphogenetic protein 4 (BMP4) activity, which determines how "robust" (i.e., the deepness and width) is the beak (Abzhanov et al. 2004, Wu et al. 2004). Calmodulin, on the other hand, appears to be the molecule whose expression levels determine elongated beaks (Abzhanov et al. 2006) (Fig. 5). The levels of these two molecules vary independently of each other, explaining the pointed beaks of cactus finch and the blunt beak of the large ground finch. In other words, the inter-individual differences in beak size were apparently related with the same genes behind the expression of proteins BMP4 and calmoduling, but differentially expressed. Then, it appears that the high quantitative genetic variation detected in several populations of Geospiza was not explained by variation in genes of small effects that codify for beak shape and size, but explained by differential levels of gene expression in the same groups of genes across populations and species. This is an example where the basic scheme does not apply: heritable variation is not a consequence of standard genetic variation. The consequences of this fact in terms of the model depicted in Fig. 1, supposing that the width and height of the beak is represented in one of the axis, and the length in the other axis, would be more complex (Fig. 6). Given that the length of the beak varíes independently of its robustness, the only limitation to a given beak shape would be the aberrant forms or physically impossible beaks. As a result, a superb amount of variation in beak shape and size is evident not only between species but also within populations (Fig. 6A). A hypothetical adaptive landscape of Darwin finches would look as in Fig. 6B, and would produce beaks as in Fig. 6C.
Fig. 5: Abzhanov an colleagues (Abzhanov et al. 2006, Abzhanov et al. 2004) discovered that the classic example of adaptive radiation in the beak of Darwin finches was not explained by the basic model of popula-tion and quantitative genetics, which supposes that selection acts on additive genetic variation (as in Fig. 1). On the contrary, they found that the shape and size of the beak in finches appear to be a function of several structural genes that do not vary in their alíele composition, but in their levels of expression. This expression is function of two factors: calmodulin (which determines beak length) and bmp4 (which controls beak height and width). Different combinations of expression of calmodulin and bmp4 produce the complete range of observed beak shapes and sizes (reproduced from Abzhanov et al. 2006, with permission from the first author and from Nature publishing group).
Abzhanov y colegas (Abzhanov et al. 2006, Abzhanov et al. 2004) descubrieron que el ejemplo clásico de radiación adaptativa en los picos de los pinzones de Darwin no estaba explicado por el modelo clásico de la genética de poblaciones y cuantitativa, el cual supone que la selección actúa sobre la variación genética aditiva (como en Fig. 1). Por el contrario, ellos encontraron que la forma y el tamaño del pico en los pinzones es función de varios genes estructurales que no varían en su composición alélica, sino que en sus niveles de expresión. Esta expresión es función de dos factores: calmodulina (que determina el largo del pico) y bmp4 (que determina el alto y ancho del pico). Diferentes combinaciones de la expresión de calmodulina y bmp4 producen el rango completo de formas y tamaños de picos (reproducido de Abzhanov et al. 2006, con permiso del primer autor y de Nature publishing group).
Fig. 6: According to Sato et al. (1999), the six species of Darwin finches of the Geospiza genus (ground finches) are monophyletic, being G. fuliginosa (small ground finch) the most basal species, which is also the less specialized. Given that the shape of the beak is generated by two gene clusters, differentially and ¡ndependently expressed (see Fig. 5), there would be a great variety of beak shapes that can be produced, even at the population level. This would be traduced in a "cloud" of breeding values without clear restrictions other than deleterious forms due to physical impossibilities (A). According to the selection gradients measured in the field, a hypothetical adaptive landscape for such situation would be B, where different diet ítems would produce several adaptive peaks, which would appear especially during dry years (see Fig. 4). This landscape would produce generalized, small beaks as is some individuals of G. fuliginosa (C: center); robust, short beaks as in some individuals of G. fortis (C: bottom, right); large, long beaks as in some individuals of G. conirostris (C: upper, right); and long beaks as G. scandens (C: upper, left).
De acuerdo a Sato et al. (1999), las seis especies de pinzones de Darwin del género Geospiza (pinzones terrestres) tienen origen monofilético, siendo G. fuliginosa (pinzón terrestre pequeño) la especie más basal, la cual es además la menos especializada. Dado que la forma del pico es generada básicamente por dos grupos de genes, expresados diferencialmente (véase Fig. 5), existirá una gran variedad de formas y tamaños de picos que se pueden generar, incluso a nivel poblacional. Esto se traduciría en una "nube" de valores de cría sin claras restricciones más que las formas deletéreas debidas a imposibilidad física (A). De acuerdo a los gradientes de selección medidos en terreno, un paisaje adaptativo hipotético en esta situación sería B, donde diferentes ítemes dietarios producirían varios picos adaptativos, los cuales aparecerían especialmente durante los años secos (véase Fig. 4). Este paisaje produciría picos generalizados y pequeños, como en algunos individuos de G. fuliginosa (C: centro); picos robustos y cortos, como en algunos individuos de G. fortis (C: abajo, derecha); picos grandes y largos, como en algunos individuos de G. conirostris (C: arriba, derecha); y picos largos como en algunos individuos de G. scandens (C: arriba, izquierda).
BEYOND THE BASIC SCHEME: EXTRAVAGANT BIOLOGY
Darwin finches are interesting examples of the application of developmental biology to understand evolutionary patterns, but it would be still within the "acceptable framework" of classic biology. In fact, ecologists and evolutionary biologists are used to observe the most varied expression of life forms, as a product of experimentally varying gene composition, and gene-expression patterns. A photosynthetic green animal would be such example, but perhaps something hard to conceive in nature. However, this is exactly what appeared in the cover of the November issue in 2008, of the Proceedings of the National Academy of Sciences. In this issue, a paper described the amazing case of a sea slug that acquires photosynthetic capacity by sequestering the chloroplasts of an alga in its digestive epithelium (Rumpho et al. 2008). This amazing case of horizontal gene transfer, in which the transferred gene is integrated into de predator's genome, is just one of several cases where genes are described to be translocated between organisms, generating evolutionary novelties at an unparalleled rate. As impressive as these examples, a myriad of alternative modes reciprocal association between genes, organisms and environment in addition to varying genotypes and gene expression patterns have been elucidated during the last decades. For instance, epigenetic inheritance or the inheritance of some acquired experience is a common phenomenon induced in early development, as DNA methylation (Jablonka & Lamb 1998, Wang & Vom Saal 2000). Dramatic evidence supports epigenetic inheritance, such as the fact that individuals who were prenatally exposed to famine during the winter of 1944-45 had, six decades later, significantly less DNA methylation of an imprinted gene compared with their unexposed, same-sex siblings (Heijmans et al. 2008). Other kinds of inheritance of acquired experience, such as adaptive anticipatory conditioning are even more spectacular, as it shows that microorganisms can learn from history, evolving the adaptive (i.e., by natural selection) capacity of anticipating environmental changes, as in Pavlov conditioning (Mitchell et al. 2009).
Genetic variation in populations, on the other hand, not only changes as consequences of classic mutation, recombination and selection forces. Several proteins are thought to produce evolutionary capacitance, a phenomenon by which genetic variation is buffered or hidden under stable condition and suddenly released under environmental changes (Le Rouzic & Carlborg 2008). Formerly, chaperones Hsp90 where identified as the main evolutionary capacitors but recently, it has been proposed to be a general consequence of complex gene networks (Bergman & Siegal 2003). A related phenomenon, genetic slippage occurs in facultative asexual organisms such as some invertebrates and plants under directional selection. In these populations, sudden episodes of sexual reproduction genérate explosions of variability and phenotypic changes contrary to the direction of previous selection (i.e., maladaptive evolution; Dickerson 1955, Lynch & Deng 1994, Deng & Lynch 1996).
Possibly the most revolutionary idea beyond the basic scheme is niche construction, and related concepts describing the impact of organism functioning on their environments. This constructivist view of evolution, in which organisms can modify their environments and "construct" their niche have been proposed several times during the last 30 years, mainly by ecologist (Jones et al. 1997), theoretical evolutionary biologists (as system-dependent selection, Lansing et al. 1998) but also by social scientists such as Cavalli-Sforza explaining cultural evolution (Vandermeer 2004). But perhaps the most well developed conceptual body, explaining how, when and at what levels niche construction is determinant for ecology and evolution is the research agenda presented by the anthropologist John Odling-Smee, the biologist Kevin Laland and the population geneticist Marcus Feldman in their book and website http://lalandlab.st-andrews.ac.uk/niche/bookoverview.html (Laland et al. 1999, Laland et al. 2001, Vandermeer 2004, Laland et al. 2008, Krakauer et al. 2009).
Niche construction is based on the idea that some consequences of organisms functioning are based on the genetics of each individual, but the temporal modifications of the gene pool and these consequences are distinct processes that are affected by natural selection. The second part of "niche construction" theory, however, indicates that the environment generates the selective pressures on genes and organism's consequences, which are themselves constructed by organisms functioning. Theoretical developments and some empirical evidence suggest that niche construction should be considered seriously as auto-organization factor which affects evolution, with consequences in all known types of ecological interaction (e.g., competence, positive interactions; Laland et al, 1999). For instance, Rezende et al. (2007) demonstrated that the (self-assembled) architecture of pollinization networks is a good predictor of extinction cascades. On the other hand, Harmon et al. (2009) demonstrated how the adaptive radiation in sticklebacks (freshwater fishes) had profound effects on ecosystem primary production, an example of how organisms modify irreversibly their global environments. In fact, Crisp et al. (2009) talked about phylogenetic biome conservatism, when referring to the tendency of species to retain their ancestral ecology, a common process in many past speciation events.
The last examples make reasonable the following question (in the context of long-term-evolutionary change) what determines what: species or ecosystems?
The task of trying to explain the enormous variety of mechanisms that the new avenues of science and technology opened in evolutionary biology is a tough one, especially when oíd paradigms are still appropriate in an enormous part of the cases. Here I tried to use examples to show how that oíd paradigms, termed the modern synthesis (or the "basic scheme", in this review) can coexist with the new possible models that explain the exotic biological phenomena outlined above. Perhaps the easiest way to see why an extended evolutionary theory is needed is to list the phenomena that were not considered to occur in the modern synthesis, some of which I just outlined: the modern synthesis does not suppose: (1) that genes are transmitted outside the generational axis, (2) that some genes have major effects, especially affecting the expression of other genes, (3) other form of inheritance than genes, (4) mechanisms of maintenance/release of genetic variation different than gene mutation and recombination, (5) that organisms can modify their environments importantly enough to be of evolutionary relevance in further generations and (6) other forms of inheritance outside organisms (e.g., niche construction) that are relevant to the evolutionary process.
I thank Fondecyt grant No 1090423 and Germán Manriquez to have kindly invited me to particípate in the simposium of Sociedad de Genética de Chile.
ABZHANOV A, WP KUO, C HARTMANN, BR GRANT, PR GRANT & CJ TABIN (2006) The calmodulin pathway and evolution of elongated beak morphology in Darwin's finches. Nature 442: 563-567. [ Links ]
ABZHANOV A, M PROTAS, BR GRANT, PR GRANT & CJ TABIN (2004) Bmp4 and morphological variation of beaks in Darwin's finches. Science 305: 1462-1465. [ Links ]
ANISIMOVA M & DA LIBERLES (2008) The quest for natural selection in the age of comparative genomics. Heredity 99: 567-579. [ Links ]
ARNOLD SJ (1983) Morphology, performance, and fitness. The American Zoologist 23: 347-361. [ Links ]
ARNOLD SJ, R BURGER, PA HOHENLOHE, BC AJIE & AG JONES (2008) Understanding the evolution and stability of the G-matrix. Evolution 62: 2451-2461. [ Links ]
ARNOLD SJ & MJ WADE (1984) On the measurement of natural and sexual selecion: Theory. Evolution 38: 709-719. [ Links ]
ARTACHO P & RF NESPOLO (2009) Natural selection reduces energy metabolism in the garden snail, Helix aspersa (Cornu aspersum). Evolution 63: 1044-1050. [ Links ]
BARBRAUD C (2000) Natural selection on body size traits in a long-lived bird, the snow petrel Pagodroma nivea. Journal of Evolutionary Biology 13: 81-88. [ Links ]
BEGIN M & DA ROFF (2001) An analysis of G matrix variation in two closely related cricket species, Gryllus firmus and G. pennsylvanicus. Journal of Evolutionary Biology 14: 1-13. [ Links ]
BEGIN M & DA ROFF (2003) The constancy of the G matrix through species divergence and the effects of quantitative genetic constraints on phenotypic evolution: A case study in crickets. Evolution 57: 1107-1120. [ Links ]
BEGIN M, DA ROFF & V DEBAT (2004) The effect of temperature and wing morphology on quantitative genetic variation in the cricket Gryllus firmus, with an appendix examining the statistical properties of the Jackknife-manova method of matrix comparison. Journal of Evolutionary Biology 17: 1255-1267. [ Links ]
BERGMAN A & ML SIEGAL (2003) Evolutionary capacitance as a general feature of complex gene networks. Nature 424: 549-552. [ Links ]
BOAG P & PR GRANT (1978) Heritability of external morphology in Darwin's finches. Nature 274: 793-794. [ Links ]
BOAG PT & PR GRANT (1981) Intense natural selection in a population of Darwin's finches (Geospizinae) in the Galapagos. Science 214: 82-85. [ Links ]
BOCHDANSKY A, P GRONKJAER, T HERRA & W LEGGETT (2005) Experimental evidence for selection against fish larvae with high metabolic rate in a food limited environment. Marine Biology 147: 1413-1417. [ Links ]
BORATYNSKI Z & P KOTEJA (2009) The association between body mass, metabolic rates and survival of bank voles. Functional Ecology 23: 330-339. [ Links ]
BRODIE ED, AJ MOORE & FJ JANZEN (1995) Visualizing and quantifying natural selection. Trends in Ecology and Evolution 10: 313-318. [ Links ]
BROMMER J, J MERILÁ, B SHELDON & L GUSTAFSSON (2005) Natural selection and genetic variation for reproductive reaction norms in wild bird populations. Evolution 59: 1362-1371. [ Links ]
BROWN JH, PA MARQUET & ML TAPER (1993) Evolution of body size: Consequences of an energetic definition of fitness. The American Naturalist 142: 573-584. [ Links ]
CANO JM, AA LAURIL, J PALO & J MERILA (2004) Population differentiation in G matrix structure due to natural selection in Rana temporaria. Evolution 58: 2013-2020. [ Links ]
CASWELL H (1989) Fitness and evolutionary demography. In: Sinauer (eds) Matrix population models: 161-177. Sinauer Associates, Sunderland, MA. [ Links ]
CEPLITIS A & O BENGTSSON (2004) Genetic variation, disequilibrium and natural selection on reproductive traits in Allium vineale. Journal of Evolutionary Biology 17: 302-311. [ Links ]
CODY ML (1966) A general theory of clutch size. Evolution 20: 174-184. [ Links ]
CONNER JK (2001) How strong is natural selection? Trends in Ecology and Evolution 16: 215-217. [ Links ]
COYNE JA, NH BARTON & M TURELLI (1997) A critique of Sewall Wright shifting balance theory of evolution. Evolution 51: 643-671. [ Links ]
COYNE JA, NH BARTON & M TURELLI (2000) Is Wright's shifting balance process important in evolution? Evolution 54: 306-317. [ Links ]
CRISP MD, MTK ARROYO, LG COOK, MA GANDOLFO, GJ JORDÁN et al. (2009) Phylogenetic biome conservatism on a global scale. Nature 458: 754-U90. [ Links ]
CROW JF (1991) Was Wright right? Science 253: 973. [ Links ]
CZARNOLESKI M, J KOZLOWSKI, G DUMIOT, JC BONNET, J MALLARD & M DUPONT-NIVET (2008) Scaling of metabolism in Helix aspersa snails: Changes through ontogeny and response to selection for increased size. Journal of Experimental Biology 211: 391-400. [ Links ]
CHEVERUD JM, JJ RUTLEDGE & WR ATCHLEY (1983) Quantitative genetics of development: Genetic correlations among age-specific trait values, and the evolution of ontogeny. Evolution 37: 895-905. [ Links ]
DENG HW & M LYNCH (1996) Change of genetic architecture in response to sex. Genetics 143: 203-212. [ Links ]
DICKERSON GE (1955) Genetic slippage in response to selection for multiple objetives. Quantitative Biology 20: 213-224. [ Links ]
DIXON AF G & P KINDLMANN (1999) Cost of flight apparatus and optimum body size of aphid migrants. Ecology 80: 1678-1690. [ Links ]
EDWARDS AWF (1994) The fundamental theorem of natural selection. Biological Reviews 69: 443-474. [ Links ]
ENDLER J (1986) Natural selection in the wild. Monographs in Population Biology 21. Princeton University Press, Oxford. [ Links ]
EWENS WJ (1989) An interpretation and proof of the fundamental theorem of natural selection. Theoretical Population Biology 36: 167-180. [ Links ]
FILCHAK KE, JB ROETHELE & JL FEDER (2000) Natural selection and sympatric divergence in the apple maggot Rhagoletis pomonella. Nature 407: 739-742. [ Links ]
FISHER RA (1930) The genetical theory of natural selection. A complete variorum edition. Oxford University Press, New York. [ Links ]
FOX CW (2000) Natural selection on seed-beetle egg size in nature and the laboratory: Variation among environments. Ecology 81: 3029-3035. [ Links ]
FRANK SA & M SLATKIN (1992) Fisher's fundamental theorem of natural selection. Trends in Ecology and Evolution 7: 92-95. [ Links ]
GADGIL M & WH BOSSERT (1970) Life historical consequences of natural selection. The American Naturalist 104: 1-23. [ Links ]
GIBBS HL & PR GRANT (1987) Oscillating selection on Darwin finches. Nature 327: 511-513. [ Links ]
GOWATY PA, I SERAGELDIN, PE PERSSON, N ELDREDGE, M LYNCH et al. (2008) Darwin 200: Great expectations. Nature 456: 317-318. [ Links ]
GRANT BR (2003) Evolution in Darwin's finches: A review of a study on Isla Daphne Major in the Galapagos Archipelago. Zoology: 255-259. [ Links ]
GRANT BR & PR GRANT (1996) High survival of Darwin's finch hybrids: Effects of beak morphology and diets. Ecology 77: 500-509. [ Links ]
GRANT BR & PR GRANT (2003) What Darwin's finches can teach us about the evolutionary origin and regulation of biodiversity. Bioscience 53: 965-975. [ Links ]
GRANT PR & BR GRANT (1994) Phenotypic and genetic-effects of hybridization in Darwins finches. Evolution 48: 297-316. [ Links ]
GRANT PR & BR GRANT (2000a) Non-random fitness variation in two populations of Darwin's finches. Proceedings of the Royal Society of London B 267: 131-138. [ Links ]
GRANT PR & BR GRANT (2000b) Quantitative genetic variation in populations of Darwin's finches. In: Mousseau TA, B Sinervo & J Endler (eds) Adaptive genetic variation in the wild: 3-40. Academic Press, New York. [ Links ]
GRANT PR & BR GRANT (2002) Unpredictable evolution in a 30-year study of Darwin's finches. Science 296: 707-711. [ Links ]
GRANT PR & BR GRANT (2006) Evolution of character displacement in Darwin's finches. Science 313: 224-226. [ Links ]
GRANT PR, BR GRANT & K PETREN (2000) The allopatric phase of speciation: The sharp-beaked ground finch (Geospiza difficilis) on the Galapagos islands. Biological Journal of the Linnean Society 69: 287-317. [ Links ]
GUBITZ T, RS THORPE & A MALHOTRA (2000) Phylogeography and natural selection in the Tenerife gecko Tarentola delalandii: Testing historical and adaptive hypotheses. Molecular Ecology 9:1213-1221. [ Links ]
GUSTAFSSON L (1986) Lifetime reproductive success and heritability: Empirical support for Fisher fundamental theorem. The American Naturalist 128: 761-764. [ Links ]
HALDANE JBS (1924) A mathematical theory of natural and artificial selection. Part I. Transactions of the Cambridge Philosophical Society 23: 19-41. [ Links ]
HALDANE JBS (1932) The causes of evolution. Princeton University Press, London. [ Links ]
HARMON LJ, B MATTHEWS, S DES ROCHES, JM CHASE, JB SHURIN & D SCHLUTER (2009) Evolutionary diversification in stickleback affects ecosystem functioning. Nature 458: 1167-1170. [ Links ]
HAYES JP & CSO O'CONNOR (1999) Natural selection on thermogenic capacity of high-altitude deer mice. Evolution 53: 1280-1287. [ Links ]
HEIJMANS BT, EW TOBI, AD STEIN, H PUTTER, GJ BLAUW, ES SUSSER, PE SLAGBOOM & LH LUMEY (2008) Persistent epigenetic differences associated with prenatal exposure to famine in humans. Proceedings of the National Academy of Sciences USA 105: 17046-17049. [ Links ]
HEY J & RM KLIMAN (2002) Interactions between natural selection, recombination and gene density in the genes of Drosophila. Genetics 160: 595-608. [ Links ]
HIGGIE M, S CHENOWETH & MW BLOWS (2000) Natural selection and the reinforcement of mate recognition. Science 290: 519-521. [ Links ]
HOEKSTRA HE, JM HOEKSTRA, D BERRIGAN, SN VIGNIERI, A HOANG, AVS HILL, P BEERLI & JG KINGSOLVER (2001) Strengh and tempo of directional selection in the wild. Proceedings of the National Academy of Science USA 98: 9157-9160. [ Links ]
HOULE D (1991) Genetic covariance of fitness correlates: What genetic correlations are made of and why it matters. Evolution 45: 630-648. [ Links ]
HOULE D (1992) Comparing evolvability and variability of quantitative traits. Genetics 130: 195-204. [ Links ]
JABLONKA E & MJ LAMB (1998) Epigenetic inheritance in evolution. Journal of Evolutionary Biology 11: 159-183. [ Links ]
JACKSON DM, P TRAYHURN & JR SPEAKMAN (2001) Associations between energetics and over-winter survival in the short-tailed field vole Microtus agrestis. Journal of Animal Ecology 70: 633-640. [ Links ]
JANZEN FJ (1993) An experimental analysis of natural selection on body size of hatchling turtles. Ecology 74: 332-341. [ Links ]
JONES AG, SJ ARNOLD & R BURGER (2003) Stability of the G- matrix in a population experiencing pleiotropic mutation, stabilizing selection, and genetic drift. Evolution 57: 1747-1760. [ Links ]
JONES CG, JH LAWTON & M SHACHAK (1997) Positive and negative effects of organisms as a physical ecosystem engineers. Ecology 78: 1946-1957. [ Links ]
KELLER L, A GRANT, BR GRANT & K PETREN (2001) Heritability of morphological traits in Darwin's finches: Misidentified paternity and maternal effects. Heredity 87: 325-336. [ Links ]
KENTNER EK & MR MESLER (2000) Evidence for natural selection in a fern hybrid zone. American Journal of Botany 87: 1168-1174. [ Links ]
KINGSOLVER JG, HE HOEKSTRA, JM HOEKSTRA, D BERRIGAN, SN VIGNIERI et al. (2001) The strength of phenotypic selection in natural populations. The American Naturalist 157: 245-261. [ Links ]
KIRK KM, SP BLOMBERG, DL DUFFY, AC HEATH, IPF OWENS & NG MARTÍN (2001) Natural selection and quantitative genetics of life-history traits in western women: A twin study. Evolution 55: 423-435. [ Links ]
KIRKPATRICK M & NH BARTON (1997) Evolution of a species range. The American Naturalist 150: 1-23. [ Links ]
KOHN MH, HJ PELZ & RK WAYNE (2000) Natural selection mapping of the warfarin-resistance gene. Proceedings of the National Academy of Sciences USA 97: 7911-7915. [ Links ]
KRAKAUER DC, KM PAGE & DH ERWIN (2009) Diversity, dilemmas, and monopolies of niche construction. American Naturalist 173: 26-40. [ Links ]
KRUUK LEB, TH CLUTTON-BROCK, J SLATE, JM PEMBERTON & S BROTHERSTONE (2000) Heritability of fitness in a wild mammal population. Proceedings of the National Academy of Sciences USA 97: 699-703. [ Links ]
KRUUK LEB, J MERILA & BC SHELDON (2001) Phenotypic selection on a heritable size trait revisited. The American Naturalist 158: 557-571. [ Links ]
KRUUK LEB, J MERILA & BC SHELDON (2003) When environmental variation short-circuits natural selection. Trends in Ecology and Evolution 18: 207-209. [ Links ]
LALAND KN, FJ ODLING-SMEE & MW FELDMAN (1999) Evolutionary consequences of niche construction and their implications for ecology. Proceedings of the National Academy of Sciences USA 96: 10242-10247. [ Links ]
LALAND KN, J ODLING-SMEE & MW FELDMAN (2001) Cultural niche construction and human evolution. Journal of Evolutionary Biology 14: 22-33. [ Links ]
LALAND KN, J ODLING-SMEE & SF GILBERT (2008) EvoDevo and niche construction: Building bridges. Journal of Experimental Zoology Part B-Molecular and Developmental Evolution 310B: 549-566. [ Links ]
LANSING JS, JN KREMER & BB SMUTS (1998) System-dependent selection, ecological feedback, and the emergence of functional structure in ecosystems. Journal of Theoretical Biology 192: 377-391. [ Links ]
LE ROUZIC A & O CARLBORG (2008) Evolutionary potential of hidden genetic variation. Trends in Ecology & Evolution 23: 33-37. [ Links ]
LEIGH EG (1999) The modern synthesis, Ronald Fisher and creationism. Trends in Ecology and Evolution 14: 495-498. [ Links ]
LINDEN M, L GUSTAFSSON & T PART (1992) Selection on fledging mass in the collared flycatcher and the great tit. Ecology 73: 336-343. [ Links ]
LYNCH M & HW DENG (1994) Genetic slippage in response to sex. The American Naturalist 144: 242-261. [ Links ]
MCADAM AG & S BOUTIN (2003) Variation in viability selection among cohorts of juvenile red squirrels (Tamiasciurus hudsonicus). Evolution 57: 1689-1697. [ Links ]
MCDONALD DB & H CASWELL (1993) Matrix methods for avian demography. In: Power D (ed) Current ornithology: 139-185. Plenum Press, New York. [ Links ]
MEDEL R (2001) Assessment of correlational selection on tolerance and resistance traits in a host plant-parasitic plant interaction. Evolutionary Ecology 15: 37-52. [ Links ]
MERILA J, LEB KRUUK & BC SHELDON (2001a) Cryptic evolution in a wild bird population. Nature 412: 76-79. [ Links ]
MERILA J, LEB KRUUK & BC SHELDON (2001b) Natural selection on the genetical component of variance in body condition in a wild bird population. Journal of Evolutionary Biology 14: 918-929. [ Links ]
MITCHELL A, GH ROMANO, B GROISMAN, A YONA, E DEKEL, M KUPIEC, O DAHAN & Y PILPEL (2009) Adaptive prediction of environmental changes by microorganisms. Nature 460: 220-U80. [ Links ]
MORRIS DW (1985) Natural selection for reproductive optima. Oikos 45: 290-293. [ Links ]
MOUSSEAU TA & DA ROFF (1987) Natural selection and the heritability of fitness components. Heredity 59: 181-197. [ Links ]
NESPOLO RF, ACC FIGUEROA, M PLANTEGENEST & JC SIMON (2008) Short-term population differences in the genetic architecture of life history traits related to sexuality in an aphid species. Heredity 100: 374-381. [ Links ]
NESPOLO RF, F HALKETT, CC FIGUEROA, M PLANTEGENEST & JC SIMON (2009) Evolution of trade-offs between sexual and asexual phases and the role of reproductive plasticity in the genetic architecture of aphid life histories. Evolution 63: 2402-2412. [ Links ]
O'DONALD P (1973) A further analysis of Bumpus' data: The intensity of natural selection. Evolution 27: 398-404. [ Links ]
OVASKAINEN O, JM CANO & J MERILA (2008) A Bayesian framework for comparative quantitative genetics. Proceedings of the Royal Society B-Biological Sciences 275: 669-678. [ Links ]
PARSONAGE S & J HUGHES (2002) Natural selection and the distribution of shell colour morphs in three species of Littoraria (Gastropoda : Littorinidae) in Moreton Bay, Queensland. Biological Journal of the Linnean Society 75: 219-232. [ Links ]
PHILLIPS PC, MC WHITLOCK & K FOWLER (2001) Inbreeding changes the shape of the genetic covariance matrix in Drosophila melanogaster. Genetics 158: 1137-1145. [ Links ]
PIGLIUCCI M (2007) Do we need an extended evolutionary synthesis? Evolution 61: 2743-2749. [ Links ]
PRICE GR (1970) Selection and covariance. Nature 227: 520-521. [ Links ]
PRICE T & LANGEN T (1992) Evolution of correlated characters. Trends in Ecology and Evolution 7: 307-310. [ Links ]
PRIMACK RB & H KANG (1989) Measuring fitness and natural selection in wild plant population. Annuals Reviews on Ecology and Systematics 20: 367-396. [ Links ]
REALE D, D BERTEAUX, AG MCADAM & S BOUTIN (2003) Lifetime selection on heritable life-history traits in a natural population of red squirrels. Evolution 57: 2416-2423. [ Links ]
REVELL LJ (2007) The G matrix under fluctuating correlational mutation and selection. Evolution 61: 1857-1872. [ Links ]
REZENDE EL, JE LAVABRE, PR GUIMARAES, P JORDANO & J BASCOMPTE (2007) Non-random coextinctions in phylogenetically structured mutualistic networks. Nature 448: 925-U6. [ Links ]
RICE WR & AK CHIPPINDALE (2001) Sexual recombination and the power of natural selection. Science 294: 555-559. [ Links ]
ROBERTSON A (1966) A mathematical model of the culling process in dairy cattle. Animal Production 8: 95-108. [ Links ]
ROFF DA (2000) The evolution of the G- matrix: Selection or drift? Heredity 84: 135-142. [ Links ]
ROFF DA & DJ FAIRBAIRN (2007) The evolution and genetics of migration in insects. Bioscience 57: 155-163. [ Links ]
RUMPHO ME, JM WORFUL, J LEE, K KANNAN, MS TYLER, D BHATTACHARYA, A MOUSTAFA & JR MANHART (2008) Horizontal gene transfer of the algal nuclear gene psbO to the photosynthetic sea slug Elysia chlorotica. Proceedings of the National Academy of Sciences USA 105: 17867-17871. [ Links ]
SALDAÑA A, CH LUSK, WL GONZÁLES & E GIANOLI (2007) Natural selection on ecophysiological traits of a fern species in a temperate rainforest. Evolutionary Ecology 21: 651-662. [ Links ]
SATO A, C O'HUIGIN, F FIGUEROA, PR GRANT, BR GRANT, H TICHY & J KLEIN (1999) Phylogeny of Darwin's finches as revealed by mtDNA sequences. Proceedings of the National Academy of Sciences USA 96: 5101-5106. [ Links ]
SCHLUTER D & JNM SMITH (1986) Natural selection on beak and body size in the song sparrow. Evolution 40: 221-231. [ Links ]
SEEHAUSEN O, Y TERAI, IS MAGALHAES, KL CARLETON, HDJ MROSSO et al. (2008) Speciation through sensory drive in cichlid fish. Nature 455: 620-U23. [ Links ]
SEELEY RH (1986) Intense natural selection caused rapid morphological transition in a living marine snail. Proceedings of the National Academy of Sciences USA 83: 6897-6901. [ Links ]
SHELDON BC, LEB KRUUK & J MERILA (2003) Natural selection and inheritance of breeding time and clutch size in the collared flycatcher. Evolution 57: 406-420. [ Links ]
SIBLY RM & P CALOW (1986) Physiological ecology of animalss: An evolutionary approach. Blackwell Scientific Publications, Oxford. [ Links ]
SINERVO B & R CALSBEEK (2003) Physiological epistasis, ontogenetic conflict and natural selection on physiology and life history. Integrative and Comparative Biology 43: 419-413. [ Links ]
SINERVO B, P DOUGHTY, RB HUEY & K ZAMUDIO (1992) Allometric engineering: A causal analysis of natural selection on offspring size. Science 258: 1927-1930. [ Links ]
SINERVO B, E SVENSSON & T COMENDANT (2000) Density cycles and an offspring quantity and quality game driven by natural selection. Nature 406: 985-988. [ Links ]
SORCI G & J CLOBERT (1999) Natural selection on hatchling body size and mass in two environments in the common lizard (Lacerta vivipara) Evolutionary Ecology Research 1: 303-316. [ Links ]
STEPPAN SJ, PC PHILLIPS & D HOULE (2002) Comparative quantitative genetics: Evolution of the G matrix. Trends in Ecology and Evolution 17: 320-327. [ Links ]
SVENSSON E & B SINERVO (2000) Experimental excursions on adaptive landscapes: Density-dependent selection on egg size. Evolution 54: 1396-1403. [ Links ]
SZEKELY T, JD REYNOLDS & J FIGUEROLA (2000) Sexual size dimorphism in shorebirds, gulls, and alcids: The influence of sexual and natural selection. Evolution 54: 1404-1413. [ Links ]
VANDERMEER J (2004) Niche construction - the neglected process in evolution. Science 303: 472-474. [ Links ]
WADE MJ & CJ GOODNIGHT (1991) Wright's shifting balance theory: An experimental study. Science 253: 1015-1019. [ Links ]
WADE MJ & CJ GOODNIGHT (1998) The theories of Fisher and Wright in the context of metapopulations: When nature does many small experiments. Evolution 52: 1537-1553. [ Links ]
WANG MH & FS VOM SAAL (2000) Maternal age and traits in offspring. Nature 407: 469-470. [ Links ]
WEINER J (2002) El pico del pinzón: Una historia de la evolución en nuestros días. Ed. Galaxia Gutenberg, Barcelona. [ Links ]
WHITFIELD J (2008) Postmodern evolution? Nature 455: 281-284. [ Links ]
WIGGINS DA (1991) Natural selection on body size and laying date in the tree swallow. Evolution 45: 1169-1174. [ Links ]
WILLIAMS GC (1966) Adaptation and natural selection. Princeton University Press, Princeton. [ Links ]
WRIGHT S (1931) Evolution in mendelian populations. Genetics 16: 97-159. [ Links ]
WRIGHT S (1932) The roles of mutation, inbreeding, crossbreeding and selection in evolution. Proceedings of The 6th International Congress in Genetics 1: 356-366. [ Links ]
WRIGHT S (1943) Isolation by distance. Genetics 28: 114-138. [ Links ]
WRIGHT S (1982) Character change, speciation, and the higher taxa. Evolution 32: 427-443. [ Links ]
WRIGHT S (1988) Surfaces of selective value revisited. The American Naturalist 131: 115-123. [ Links ]
WU P, TX JIANG, S SUKSAWEANG, RB WIDELITZ & CM CHUONG (2004) Molecular shaping of the beak. Science 305: 1465-1466. [ Links ]
Invited Associate Editor: Germán Manríquez
Received February 3, 2010; accepted August 20, 2010