The adaptive landscape of science

In 1988, David Hull presented an evolutionary account of science. This was a direct analogy to evolutionary accounts of biological adaptation, and part of a generalized view of Darwinian selection accounts that he based upon the Universal Darwinism of Richard Dawkins. Criticisms of this view were made by, among others, Kim Sterelny, which led to it gaining only limited acceptance. Some of these criticisms are, I will argue, no longer valid in the light of developments in the formal modeling of evolution, in particular that of Sergey Gavrilets’ work on adaptive landscapes. If we can usefully recast the Hullian view of science as being driven by selection in terms of Gavrilets’ and Kaufmann’s view of there being “giant components” of high-fitness networks through any realistic adaptive landscape, we may now find it useful to ask what the adaptive pressures on science are, and to extend the metaphor into a full analogy. This is in effect to reconcile the Fisherianism of the Dawkins–Hull approach to selection and replicators, with a Wrightean drift account of social constructionist views of science, preserving, it is to be hoped, the valuable aspects of both.

Optimality modeling in a suboptimal world

The fate of optimality modeling is typically linked to that of adaptationism: the two are thought to stand or fall together (Gould and Lewontin, Proc Relig Soc Lond 205:581–598, 1979; Orzack and Sober, Am Nat 143(3):361–380, 1994). I argue here that this is mistaken. The debate over adaptationism has tended to focus on one particular use of optimality models, which I refer to here as their strong use. The strong use of an optimality model involves the claim that selection is the only important influence on the evolutionary outcome in question and is thus linked to adaptationism. However, biologists seldom intend this strong use of optimality models. One common alternative that I term the weak use simply involves the claim that an optimality model accurately represents the role of selection in bringing about the outcome. This and other weaker uses of optimality models insulate the optimality approach from criticisms of adaptationism, and they account for the prominence of optimality modeling (broadly construed) in population biology. The centrality of these uses of optimality models ensures a continuing role for the optimality approach, regardless of the fate of adaptationism.

Biological Levers and Extended Adaptationism

Two critiques of simple adaptationism are distinguished: anti-adaptationism and extended adaptationism. Adaptationists and anti-adaptationists share the presumption that an evolutionary explanation should identify the dominant simple cause of the evolutionary outcome to be explained. A consideration of extended-adaptationist models such as coevolution, niche construction and extended phenotypes reveals the inappropriateness of this presumption in explaining the evolution of certain important kinds of features—those that play particular roles in the regulation of organic processes, especially behavior. These biological or behavioral ‘levers’ are distinctively available for adaptation and exaptation by their possessors and for co-optation by other organisms. As a result they are likely to result from a distinctive and complex type of evolutionary process that conforms neither to simple adaptationist nor to anti-adaptationist styles of explanation. Many of the human features whose evolutionary explanation is most controversial belong to this category, including the female orgasm.

Feather evolution exemplifies sexually selected bridges across the adaptive landscape

Over the last two decades, paleontologists have pieced together the early evolutionary history of feathers. Simple hair‐like feathers served as insulating pelage, but the first feathers with complex branching structures and a plainer form evolved for the purpose of sexual display. The evolution of these complex display feathers was essential to the later evolution of flight. Feathers illustrate how sexual selection can generate complex novel phenotypes, which are then available for natural selection to modify and direct toward novel functions. In the longstanding metaphor of the adaptive landscape, sexual selection is a means by which lineages resting on one adaptive peak may gradually bridge a gap to another peak, without the landscape itself being first altered by environmental changes.     

Properties of adaptive walks on uncorrelated landscapes under strong selection and weak mutation

We examine properties of adaptive walks on uncorrelated (i.e. random) fitness landscapes starting from moderately fit genotypes under strong selection weak mutation. As an extension of Orr's model for a single step in an adaptive walk under these conditions, we show that the fitness rank of the dominant genotype in a population after the fixation of a beneficial mutation is, on average, (i+6)/4, where i is the fitness rank of the starting genotype. This accounts for the change in rank due to acquiring a new set of single-mutation neighbors after fixing a new allele through natural selection. Under this scenario, adaptive walks can be modeled as a simple Markov chain on the space of possible fitness ranks with an absorbing state at i = 1, from which no beneficial mutations are accessible. We find that these walks are typically short and are often completed in a single step when starting from a moderately fit genotype. As in Orr's original model, these results are insensitive to both the distribution of fitness effects and most biological details of the system under consideration.     

Synthetic shuffling and in vitro selection reveal the rugged adaptive fitness landscape of a kinase ribozyme

The relationship between genotype and phenotype is often described as an adaptive fitness landscape. In this study, we used a combination of recombination, in vitro selection, and comparative sequence analysis to characterize the fitness landscape of a previously isolated kinase ribozyme. Point mutations present in improved variants of this ribozyme were recombined in vitro in more than 10¹⁴ different arrangements using synthetic shuffling, and active variants were isolated by in vitro selection. Mutual information analysis of 65 recombinant ribozymes isolated in the selection revealed a rugged fitness landscape in which approximately one-third of the 91 pairs of positions analyzed showed evidence of correlation. Pairs of correlated positions overlapped to form densely connected networks, and groups of maximally connected nucleotides occurred significantly more often in these networks than they did in randomized control networks with the same number of links. The activity of the most efficient recombinant ribozyme isolated from the synthetically shuffled pool was 30-fold greater than that of any of the ribozymes used to build it, which indicates that synthetic shuffling can be a rich source of ribozyme variants with improved properties.     

The standard genetic code enhances adaptive evolution of proteins

The standard genetic code, by which most organisms translate genetic material into protein metabolism, is non-randomly organized. The Error Minimization hypothesis interprets this non-randomness as an adaptation, proposing that natural selection produced a pattern of codon assignments that buffers genomes against the impact of mutations. Indeed, on the average any given point mutation has a lesser effect on the chemical properties of the utilized amino acid than expected by chance. Might it also, however, be the case that the non-random nature of the code effects the rate of adaptive evolution? To investigate this, here we develop population genetic simulations to test the rate of adaptive gene evolution under different genetic codes. We identify two independent properties of a genetic code that profoundly influence the speed of adaptive evolution. Noting that the standard genetic code exhibits both, we offer a new insight into the effects of the "error minimizing" code: such a code enhances the efficacy of adaptive sequence evolution.     

Evolution and stability of the G-matrix on a landscape with a moving optimum

In quantitative genetics, the genetic architecture of traits, described in terms of variances and covariances, plays a major role in determining the trajectory of evolutionary change. Hence, the genetic variance-covariance matrix (G-matrix) is a critical component of modern quantitative genetics theory. Considerable debate has surrounded the issue of G-matrix constancy because unstable G-matrices provide major difficulties for evolutionary inference. Empirical studies and analytical theory have not resolved the debate. Here we present the results of stochastic models of G-matrix evolution in a population responding to an adaptive landscape with an optimum that moves at a constant rate. This study builds on the previous results of stochastic simulations of G-matrix stability under stabilizing selection arising from a stationary optimum. The addition of a moving optimum leads to several important new insights. First, evolution along genetic lines of least resistance increases stability of the orientation of the G-matrix relative to stabilizing selection alone. Evolution across genetic lines of least resistance decreases G-matrix stability. Second, evolution in response to a continuously changing optimum can produce persistent maladaptation for a correlated trait, even if its optimum does not change. Third, the retrospective analysis of selection performs very well when the mean G-matrix (G) is known with certainty, indicating that covariance between G and the directional selection gradient beta is usually small enough in magnitude that it introduces only a small bias in estimates of the net selection gradient. Our results also show, however, that the contemporary G-matrix only serves as a rough guide to G. The most promising approach for the estimation of G is probably through comparative phylogenetic analysis. Overall, our results show that directional selection actually can increase stability of the G-matrix and that retrospective analysis of selection is inherently feasible. One major remaining challenge is to gain a sufficient understanding of the G-matrix to allow the confident estimation of G.     

The adaptive landscape as a conceptual bridge between micro- and macroevolution

An adaptive landscape concept outlined by G.G. Simpson constitutes the major conceptual bridge between the fields of micro- and macroevolutionary study. Despite some important theoretical extensions since 1944, this conceptual bridge has been ignored in many empirical studies. In this article, we review the status of theoretical work and emphasize the importance of models for peak movement. Although much theoretical work has been devoted to evolution on stationary, unchanging landscapes, an important new development is a focus on the evolution of the landscape itself. We also sketch an agenda of empirical issues that is inspired by theoretical developments.     

The nature of developmental constraints and the difference-maker argument for externalism

One current version of the internalism/externalism debate in evolutionary theory focuses on the relative importance of developmental constraints in evolutionary explanation. The received view of developmental constraints sees them as an internalist concept that tend to be shared across related species as opposed to selective pressures that are not. Thus, to the extent that constraints can explain anything, they can better explain similarity across species, while natural selection is better able to explain their differences. I challenge both of these aspects of the received view and propose a hierarchical view of constraints.

Sewall Wright’s adaptive landscapes: 1932 vs. 1988

Sewall Wright introduced the metaphor of evolution on “adaptive landscapes” in a pair of papers published in 1931 and 1932. The metaphor has been one of the most influential in modern evolutionary biology, although recent theoretical advancements show that it is deeply flawed and may have actually created research questions that are not, in fact, fecund. In this paper I examine in detail what Wright actually said in the 1932 paper, as well as what he thought of the matter at the very end of his career, in 1988. While the metaphor is flawed, some of the problems which Wright was attempting to address are still with us today, and are in the process of being reformulated as part of a forthcoming Extended Evolutionary Synthesis.

Defining the landscape of adaptive genetic diversity

Whether they are used to describe fitness, genome architecture or the spatial distribution of environmental variables, the concept of a landscape has figured prominently in our collective reasoning. The tradition of landscapes in evolutionary biology is one of fitness mapped onto axes defined by phenotypes or molecular sequence states. The characteristics of these landscapes depend on natural selection, which is structured across both genomic and environmental landscapes, and thus, the bridge among differing uses of the landscape concept (i.e. metaphorically or literally) is that of an adaptive phenotype and its distribution across geographical landscapes in relation to selective pressures. One of the ultimate goals of evolutionary biology should thus be to construct fitness landscapes in geographical space. Natural plant populations are ideal systems with which to explore the feasibility of attaining this goal, because much is known about the quantitative genetic architecture of complex traits for many different plant species. What is less known are the molecular components of this architecture. In this issue of Molecular Ecology, Parchman et al. (2012) pioneer one of the first truly genome-wide association studies in a tree that moves us closer to this form of mechanistic understanding for an adaptive phenotype in natural populations of lodgepole pine (Pinus contorta Dougl. ex Loud.).     

Source-sink landscape theory and its ecological significance

Exploring the relatiouships between landscape pattern and ecological processes is the key topic of landscape ecology,for which,a large number of indices as well as landscape pattern analysis model were developed.However,one problem faced by landscape ecologists is that it is hard to link the landscape indices with a specific ecological process.Linking landscape pattern and ecological processes has become a challenge for landscape ecologists."Source" and "sink" are common concepts used in air pollution research,by which the movement direction and pattern of different pollutants in air can be clearly identified.In fact,for any ecological process,the research can be considered as a balance between the source and the sink in space.Thus,the concepts of "source" and "sink" could be implemented to the research of landscape pattern and ecological processes.In this paper,a theory of sourcesink landscape was proposed,which include:(1) In the research of landscape pattern and ecological process,all landscape types can be divided into two groups,"source"landscape and "sink" landscape."Source" landscape contributes positively to the ecological process,while "sink" landscape is unhelpful to the ecological process.(2) Both landscapes are recognized with regard to the specific ecological process."Source" landscape in a target ecological process may change into a "sink"landscape as in another ecological process.Therefore,the ecological process should be determined before "source"or "sink" landscape were defined.(3) The key point to distinguish "source" landscape from "sink" landscape is to quantify the effect of landscape on ecological process.The positive effect is made by "source" landscape,and the negative effect by "sink" landscape.(4) For the same ecological process,the contribution of "source" landscapes may vary,and it is the same to the "sink"landscapes.It is required to determine the weight of each landscape type on ecological processes.(5) The sourcesink principle can be applied to non-point source pollution control,biologic diversity protection,urban heat island effect mitigation,etc.However,the landscape evaluation models need to be calibrated respectively,because different ecological processes correspond with different source-sink landscapes and evaluation models for the different study areas.This theory is helpful to further study landscape pattern and ecological process,and offers a basis for new landscape index design.     

“源”“汇”景观理论及其生态学意义

格局与过程的关系是景观生态学研究中的核心内容.景观格局指数是定量分析景观格局与生态过程的主要方法,但由于许多景观格局指数难以将格局与过程有机融合在一起而陷入困境,探讨景观格局分析中有效表征生态过程的理论与方法,对于景观生态学的发展具有积极意义.基于大气污染中的“源”“汇”理论,在已有研究基础上,提出了“源”“汇”景观的概念和理论.认为根据不同景观类型的功能,可以将他们划分为“源”“汇”两种景观类型,从而将过程的内涵融于景观格局分析中.该理论认为：（1）在格局与过程研究中,异质景观可以分为“源”“汇”景观两种类型,其中“源”景观是指那些能促进过程发展的景观类型,“汇”景观是那些能阻止或延缓过程发展的景观类型;（2）“源”“汇”景观的性质是相对的,对于某一过程的“源”景观,可能是另一过程的“汇”景观,“源”“汇”景观的分析必须针对特定的过程;（3）“源”“汇”景观区分的关键在于判断景观类型在生态过程演变中所起的作用,是正向推动作用还是负向滞缓作用;（4）不同类型“源”（或者“汇”）景观对于同一种生态过程的贡献是不同的,在分析景观格局对生态过程的影响时需要考虑这种作用的差异;（5）“源”“汇”景观理论可以应用于非点源污染、生物多样性保护、城市热岛效应等不同领域.“源”“汇”景观理论提出的主要目的是探究不同景观类型在空间上的动态平衡对生态过程影响,从而找到适合一个地区的景观空间格局.这一理论的提出有助于推动景观格局与生态过程研究的深入,希望以此为基础,通过大量的实证研究,丰富和完善“源”、“汇”景观的理论和方法.     

Source-sink landscape theory and its ecological significance

Exploring the relationships between landscape pattern and ecological processes is the key topic of landscape ecology, for which, a large number of indices as well as landscape pattern analysis model were developed. However, one problem faced by landscape ecologists is that it is hard to link the landscape indices with a specific ecological process. Linking landscape pattern and ecological processes has become a challenge for landscape ecologists. “Source” and “sink” are common concepts used in air pollution research, by which the movement direction and pattern of different pollutants in air can be clearly identified. In fact, for any ecological process, the research can be considered as a balance between the source and the sink in space. Thus, the concepts of “source” and “sink” could be implemented to the research of landscape pattern and ecological processes. In this paper, a theory of sourcesink landscape was proposed, which include: (1) In the research of landscape pattern and ecological process, all landscape types can be divided into two groups, “source” landscape and “sink” landscape. “Source” landscape contributes positively to the ecological process, while “sink” landscape is unhelpful to the ecological process. (2) Both landscapes are recognized with regard to the specific ecological process. “Source” landscape in a target ecological process may change into a “sink” landscape as in another ecological process. Therefore, the ecological process should be determined before “source” or “sink” landscape were defined. (3) The key point to distinguish “source” landscape from “sink” landscape is to quantify the effect of landscape on ecological process. The positive effect is made by “source” landscape, and the negative effect by “sink” landscape. (4) For the same ecological process, the contribution of “source” landscapes may vary, and it is the same to the “sink” landscapes. It is required to determine the weight of each landscape type on ecological processes. (5) The sourcesink principle can be applied to non-point source pollution control, biologic diversity protection, urban heat island effect mitigation, etc. However, the landscape evaluation models need to be calibrated respectively, because different ecological processes correspond with different source-sink landscapes and evaluation models for the different study areas. This theory is helpful to further study landscape pattern and ecological process, and offers a basis for new landscape index design. __________ Translated from Acta Ecologica Sinica, 2006, 26(5): 1444–1449 [译自: 生态学报]     

Perspective: detecting adaptive molecular polymorphism: lessons from the MHC

Abstract. In the 1960s, when population geneticists first began to collect data on the amount of genetic variation in natural populations, balancing selection was invoked as a possible explanation for how such high levels of molecular variation are maintained. However, the predictions of the neutral theory of molecular evolution have since become the standard by which cases of balancing selection may be inferred. Here we review the evidence for balancing selection acting on the major histocompatibility complex (MHC) of vertebrates, a genetic system that defies many of the predictions of neutrality. We apply many widely used tests of neutrality to MHC data as a benchmark for assessing the power of these tests. These tests can be categorized as detecting selection in the current generation, over the history of populations, or over the histories of species. We find that selection is not detectable in MHC datasets in every generation, population, or every evolutionary lineage. This suggests either that selection on the MHC is heterogeneous or that many of the current neutrality tests lack sufficient power to detect the selection consistently. Additionally, we identify a potential inference problem associated with several tests of neutrality. We demonstrate that the signals of selection may be generated in a relatively short period of microevolutionary time, yet these signals may take exceptionally long periods of time to be erased in the absence of selection. This is especially true for the neutrality test based on the ratio of nonsynonymous to synonymous substitutions. Inference of the nature of the selection events that create such signals should be approached with caution. However, a combination of tests on different time scales may overcome such problems.     

Water and molecular chaperones act as weak links of protein folding networks: energy landscape and punctuated equilibrium changes point towards a game theory of proteins

Water molecules and molecular chaperones efficiently help the protein folding process. Here we describe their action in the context of the energy and topological networks of proteins. In energy terms water and chaperones were suggested to decrease the activation energy between various local energy minima smoothing the energy landscape, rescuing misfolded proteins from conformational traps and stabilizing their native structure. In kinetic terms water and chaperones may make the punctuated equilibrium of conformational changes less punctuated and help protein relaxation. Finally, water and chaperones may help the convergence of multiple energy landscapes during protein-macromolecule interactions. We also discuss the possibility of the introduction of protein games to narrow the multitude of the energy landscapes when a protein binds to another macromolecule. Both water and chaperones provide a diffuse set of rapidly fluctuating weak links (low affinity and low probability interactions), which allow the generalization of all these statements to a multitude of networks.     

Context dependence in complex adaptive landscapes: frequency and trait‐dependent selection surfaces within an adaptive radiation of Caribbean pupfishes

The adaptive landscape provides the foundational bridge between micro‐ and macroevolution. One well‐known caveat to this perspective is that fitness surfaces depend on ecological context, including competitor frequency, traits measured, and resource abundance. However, this view is based largely on intraspecific studies. It is still unknown how context‐dependence affects the larger features of peaks and valleys on the landscape which ultimately drive speciation and adaptive radiation. Here, I explore this question using one of the most complex fitness landscapes measured in the wild in a sympatric pupfish radiation endemic to San Salvador Island, Bahamas by tracking survival and growth of laboratory‐reared F2 hybrids. I present new analyses of the effects of competitor frequency, dietary isotopes, and trait subsets on this fitness landscape. Contrary to expectations, decreasing competitor frequency increased survival only among very common phenotypes, whereas less common phenotypes rarely survived despite few competitors, suggesting that performance, not competitor frequency, shapes large‐scale features of the fitness landscape. Dietary isotopes were weakly correlated with phenotype and growth, but did not explain additional survival variation. Nonlinear fitness surfaces varied substantially among trait subsets, revealing one‐, two‐, and three‐peak landscapes, demonstrating the complexity of selection in the wild, even among similar functional traits.     

Molecular population genetics and the search for adaptive evolution in plants

The first papers on plant molecular population genetics were published approximately 10 years ago. Since that time, well over 50 additional studies of plant nucleotide polymorphism have been published, and many of these studies focused on detecting the signature of balancing or positive selection at a locus. In this review, we discuss some of the theoretical and statistical issues surrounding the detection of selection, with focus on plant populations, and we also summarize the empirical plant molecular population genetics literature. At face value, the literature suggests that a history of balancing or positive selection in plant genes is rampant. In two well-studied taxa (maize and Arabidopsis) over 20% of studied genes have been interpreted as containing the signature of selection. We argue that this is probably an overstatement of the prevalence of natural selection in plant genomes, for two reasons. First, demographic effects are difficult to incorporate and have generally not been well integrated into the plant population genetics literature. Second, the genes studied to date are not a random sample, so selected genes may be overrepresented. The next generation of studies in plant molecular population genetics requires additional sampling of local populations, explicit comparisons among loci, and improved theoretical methods to control for demography. Eventually, candidate loci should be confirmed by explicit consideration of phenotypic effects.     

Geographic variation in the adaptive landscape for seed size at dispersal in the myrmecochorous <Emphasis Type="Italic">Helleborus foetidus</Emphasis>

Literature on seed dispersal mutualisms suggests that plant populations should hardly adapt to their current dispersers. We address the predictions that selection pressures exerted by ants on dispersal-related diaspore traits of the ant-dispersed Helleborus foetidus are highly variable in space, and that geographic (inter-population) variation in these traits is unrelated to selection by current dispersers. To test these predictions we use the concept of the quantitative adaptive landscape for seed size at dispersal. Such landscape depicts the relationship between the population’s mean trait value (mean seed size in the present study) and the population’s mean fitness (mean dispersal probability in the present study). Adaptive landscapes make it possible to assess whether the mean population’s phenotype agrees with one favored by selection. We first analyse, in 12 populations of H. foetidus from southern Spain, the extent of divergence among populations in seed and elaiosome size, and the abundance, composition, and behavior of the ant communities. Seeds from a fixed set of five of these populations were offered to ants in all the study sites to fit the adaptive landscape for seed size. In addition, seeds from the local population were also offered in each site. Our results show that seed size has undergone a larger divergence among populations than elaiosome size. Despite geographic variation in ant assemblages, the adaptive landscapes for seed size at dispersal were remarkably similar among sites: ants create disruptive selection on seed size in 10 out of 12 study sites. As predicted, the basic features of these adaptive landscapes (curvature and location of the minimum) varied geographically in accordance with variation in the size of seed dispersers. Also as predicted, in most populations, the observed mean seed size does not agree with that expected from the adaptive landscapes at dispersal. However, the relevance of dispersers for seed size evolution should not be neglected since the agreement between observed and optimum seed size was stronger where dispersers were more abundant. Thus, against the general view, our results evidence that, in H. foetidus, the observed geographic variation in dispersal-related plant traits is partly linked to selection exerted by current dispersers. Geographic variation in ant assemblages determines both the existence of a selection mosaic and the degree of adjustment of populations to the patterns of selection in the mosaic.