Evolution by natural induction

Natural induction is a different adaptive mechanism from natural selection. It occurs in dynamical systems described by a network of interactions, where connections give way slightly under stress and the system is subject to occasional perturbations. Various biological systems (from gene-regulation networks, to metabolic networks, to ecosystems) meet these basic conditions and therefore have potential to exhibit adaptation by natural induction. In this pair of papers, we consider various ways that natural induction and natural selection might interact. In a scenario of induction-first evolution, discussed in the first paper, a phenotypic adaptation is clearly not a product of natural selection because it appears before any genetic evolution has taken place. This paper discusses more subtle cases, where an interaction of both natural selection and natural induction is involved in producing adaptations. Nonetheless, natural selection alone does not explain these adaptations because they occur at scales where natural selection does not apply. Specifically, in the case of ecosystem adaptation, natural selection does not apply at that organizational scale. And in the evolution of evolvability, natural selection does not apply at the relevant temporal scale. We conclude that evolution by natural induction is a viable process that expands our understanding of evolutionary adaptation.

Extreme environments and adaptation.- The evolution of plants in metal-contaminated environments.- Responses of aquatic organisms to pollutant stress: Theoretical and practical implications.- Conifers from the cold.- Genetic variation and environmental stress.- Phenotypic plasticity and fluctuating asymmetry as responses to environmental stress in the butterflyBicyclus anynana.- Environmental stress and the expression of genetic variation.- Worldwide latitudinal clines for the alcohol dehydrogenase polymorphism in Drosophila melanogaster: What is the unit of selection?.- Stress and metabolic regulation inDrosophila.- Acclimation and response to thermal stress.- Phenotypic and evolutionary adaptation of a model bacterial system to stressful thermal environments.- Ecological and evolutionary physiology of heat shock proteins and the stress response inDrosophila: Complementary insights from genetic engineering and natural variation.- High-temperature stress and the evolution of thermal resistance inDrosophila.- Stress, selection and extinction.- Genetic and environmental stress, and the persistence of populations.- Adaptation and extinction in changing environments.- Environmental stress and evolution: A theoretical study.- Stress, developmental stability and sexual selection.- Evolution and stress.- Genetic variability and adaptation to stress.- Stress-resistance genotypes, metabolic efficiency and interpreting evolutionary change.- The Plus ca change model: Explaining stasis and evolution in response to abiotic stress over geological timescales.

The recognition that evolution can happen on ecological timescales (Hairston et al. 2005; Pelletier et al. 2009; Ellner et al. 2011; Becks et al. 2012) has prompted the integration of ecology and evolution, while easier access to high-throughput sequencing technologies has increased the number of genetic nonmodel species entering the ‘omics’ era (e.g. Turner et al. 2010; Colbourne et al. 2011; Jones et al. 2012). We are now in a position to identify the genetic basis of adaptation and the mechanisms of adaptive responses in the wild. It nonetheless remains a challenge to go beyond descriptive measures of patterns of genetic variation and to identify the evolutionary processes driving species adaptation and evolution. This special issue represents a broad cross-section of research into evolutionary adaptation at the genetic level. The approaches used vary from classic QTL studies to RAD sequencing and RNAseq. Given the rapid advance of sequencing technology, we fully expect that ‘genomic’ as defined here will be merely ‘genetic’ in a few years, but we nonetheless hope that the results and methods described in this special issue will serve as a blueprint for future work in this field.

Denis Noble, Eva Jablonka, Michael J. Joyner, Gerd B. Muller and Stig W. Omholt University of Oxford, Department of Physiology, Anatomy and Genetics, Oxford, UK Tel Aviv University, Cohn Institute for the History andPhilosophyof Science and Ideas, Ramat Aviv, Israel Mayo Clinic, Rochester, MN, USA University of Vienna, Department of Theoretical Biology, Vienna, Austria Norwegian University of Science and Technology, Faculty of Medicine, Trondheim, Norway

When Charles Darwin was developing his ideas for On the Origin of Species, the most widely accepted estimates of Earth’s age were those of William Thomson (later Lord Kelvin). Kelvin used calculations involving thermodynamics to argue that Earth is only 20–100 million years old—an age far too brief to accommodate evolution by natural selection. Darwin referred to Thomson’s claim as one of his “sorest troubles,” for Darwin understood that the history of life on Earth ultimately relies on geology. Darwin suspected that Earth was much older than Thomson claimed, but Thomson’s enormous stature as a scientist obliged Darwin to reconcile his claims with Kelvin’s data. To accommodate Kelvin’s timeline, Darwin proposed pangenesis as an explanation of inheritance (i.e., every sperm and egg contained “gemmules thrown off from each different unit throughout the body”). Darwin’s explanation sped evolution while avoiding Lamarck’s quasi-spiritual sources of acquired traits. However, Darwin’s explanation of inheritance was wrong (see discussion in Moore et al. 2009a). The age of Earth remains a divisive topic in the modern evolution–creationism controversy. Whereas mainstream science has long acknowledged that Earth is approximately 4.5 billion years old, a vocal group of citizens and religious activists continue to insist that Earth is less than 10,000 years old. Although most geocentrists and flat-Earth advocates have capitulated to scientific evidence, young-Earth creationists continue to reject scientific evidence in favor of religious dictum to claim that Earth is less than 10,000 years old. These antiscience claims have been surprisingly popular with the public. For example, a Gallup Poll in early 2009 reported that “On Darwin’s [200th] Birthday, Only 4 in 10 Believe in Evolution” (Newport 2009), and Berkman et al. (2008) noted that “16% [of biology teachers] believed that human beings were created by God in their present form at one time within the last 10,000 years.” In another study, 12.5% of students were young-Earth creationists (Rutledge and Warden 2000), as are 10%–14% of biology majors (Moore and Cotner 2009). Answers in Genesis’ (AiG) Creation Museum, along with the $27 million in donations required to build it, attest to the appeal of young-Earth creationism. Indeed, AiG’s income for 2005 exceeded $13 million, and that of the Institute for Creation Research (ICR, another religious organization based on young-Earth creationism) exceeded $7 million. For comparison, the 2005 income of National Center for Science Education—the nation’s leading organization that defends the teaching of evolution in public schools—was

Rapid diversification is common among herbivorous insects and is often the result of host shifts, leading to the exploitation of novel food sources. This, in turn, is associated with adaptive evolution of female oviposition behavior and larval feeding biology. Although natural selection is the typical driver of such adaptation, the role of sexual selection is less clear. In theory, sexual selection can either accelerate or impede adaptation. To assess the independent effects of natural and sexual selection on the rate of adaptation, we performed a laboratory natural selection experiment in a herbivorous bruchid beetle (Callosobruchus maculatus). We established replicated selection lines where we varied natural (food type) and sexual (mating system) selection in a 2 x 2 orthogonal design, and propagated our lines for 35 generations. In half of the lines, we induced a host shift whereas the other half was kept on the ancestral host. We experimentally enforced monogamy in half of the lines, whereas the other half remained polygamous. The beetles rapidly adapted to the novel host, which primarily involved increased host acceptance by females and an accelerated rate of larval development. We also found that our mating system treatment affected the rate of adaptation, but that this effect was contingent upon food type. As beetles adapted to the novel host, sexual selection reinforced natural selection whereas populations residing close to their adaptive peak (i.e., those using their ancestral host) exhibited higher fitness in the absence of sexual selection. We discuss our findings in light of current sexual selection theory and suggest that the net evolutionary effect of reproductive competition may critically depend on natural selection. Sexual selection may commonly accelerate adaptation under directional natural selection whereas sexual selection, and the associated load brought by sexual conflict, may tend to depress population fitness under stabilizing natural selection.

Automated synthesis refers to design of physical systems using any of the models proposed for machine intelligence like evolutionary computation, neural networks and fuzzy logic. Mechatronic systems arc mixed or hybrid systems as thcy combine elements from different cncrgy domains. These dynamic systems are inherently complex and capturing underlying energy behavior among interacting sub-systems is difficult owing to the variety in the composition of the mechatronic systems and also due to the limitation imposed by conventional modeling techniques unable to handle more than one energy domain. Bond-Graph modeling and simulation is an advanced domain independent, object oriented and polymorphic graphical description of physical systems. The universal modeling paradigm offered by Bond-Graphs is well suited for mcchatronic systems as it can represent their multi energy domain character using a unified notation scheme. Genetic programming is one of the most promising evolutionary computation techniques. The genetic programming paradigm is modeled on Darwinian concepts of evolution and natural selection. Genetic programming starts from a high level statement of a problem's requirements along with a fitness criterion and attempts to produce a computer program that provides a solution to the problem. Combining unified modeling and analysis tools offered by Bond-Graphs with topologically open ended synthesis and search capability of genetic programming, a novel automated design methodology has been developed for generating mechatronic systems designs using an integrated synthesis, analysis and feedback scheme which comes close to the definition of a true automated invention machine. This research paper is a brief introduction to all concepts associated with automated design of mechatronic systems using Bond-Graphs and genetic programming and explains the novel automated design methodology with a design example.

A number of scholars have suggested that religion may be explained using evolutionary theory and, in particular, natural selection. Much of this research suggests that behaviors encouraged by religions are beneficial while failing to illustrate a causal relationship between religiosity and these behaviors. This chapter challenges these approaches, arguing that religion is primarily a social phenomenon and that any health or evolutionary benefits that might indirectly derive from religions are actually attributable to the behaviors themselves: Religions have simply co-opted those behaviors. Additionally, it argues that natural selection alone is a problematic approach to understanding religion and suggests that Darwin’s notion of artificial selection be integrated into any attempts to use evolution to explain religion. We use examples from a variety of religions to illustrate how a socioevolutionary theory of religion that incorporates natural and artificial selection is preferable to approaches that rely exclusively on natural selection.

Evolution by natural selection is believed to be the only possible source of spontaneous adaptive organisation in the natural world. This places strict limits on the kinds of systems that can exhibit adaptation spontaneously, i.e., without design. Physical systems can show some properties relevant to adaptation without natural selection or design. (1) The relaxation, or local energy minimisation, of a physical system constitutes a natural form of optimisation insomuch as it finds locally optimal solutions to the frustrated forces acting on it or between its components. (2) When internal structure 'gives way' or accommodates a pattern of forcing on a system, this constitutes learning insomuch, as it can store, recall, and generalise past configurations. Both these effects are quite natural and general, but in themselves insufficient to constitute non-trivial adaptation. However, here we show that the recurrent interaction of physical optimisation and physical learning together results in significant spontaneous adaptive organisation. We call this adaptation by natural induction. The effect occurs in dynamical systems described by a network of viscoelastic connections subject to occasional disturbances. When the internal structure of such a system accommodates slowly across many disturbances and relaxations, it spontaneously learns to preferentially visit solutions of increasingly greater quality (exceptionally low energy). We show that adaptation by natural induction thus produces network organisations that improve problem-solving competency with experience (without supervised training or system-level reward). We note that the conditions for adaptation by natural induction, and its adaptive competency, are different from those of natural selection. We therefore suggest that natural selection is not the only possible source of spontaneous adaptive organisation in the natural world.

It is tempting to believe that humans, owing to their technological prowess, have elevated themselves above the laws of biology and escaped natural selection. Indeed, some think that humans have stopped evolving at all. Another view holds that Homo sapiens has not isolated itself from the influences of the physical and biological world but that our species is just a special, extreme case of niche constructors. This view is based on the so‐called Niche Construction Theory, a development within evolutionary biology to describe how humans—and many other organisms—modify their environment—or niche—in a way that alters environmental pressures and therefore natural selection. Thus, rather adapting to a pre‐existing environment, “organisms drive environmental change and organism‐modified environments subsequently select organisms” (https://synergy.st-andrews.ac.uk/niche/niche-construction-and-evolution/) (Box 1). ### Culture‐driven evolution “[All] organisms adapt to their environment, and in humans much of our environment is defined by our culture. Hence, cultural change can actually spur on adaptive evolution in humans”, wrote evolutionary biologist Alan Templeton at Washington University in St. Louis, MO, USA. [1]. Following this argument, culture, social learning and technology have not replaced biological adaptation. Rather, human evolution is driven by the environmental conditions we created ourselves through culture, a process that has been accelerating since the beginning of agriculture and urban civilization. In other words, cultural niche construction is a major cause of recent human evolution. However, there are other factors than natural selection, such as genetic drift and gene flow, that influence human evolution [1]. Nonetheless, even the effects of these random, non‐adaptive forces on human genetic variation are somehow altered by cultural trends, namely increased urbanization and greater mobility. As a consequence, drift is diminishing and gene flow is increasing, a process that would eventually culminate into a single “species‐wide” gene pool characterized by high levels of genetic variation. > [C]ulture, …

According to neo-Darwinian theory, biological evolution is produced by natural selection of random hereditary variations. This assumption stems from the idea of a mechanical and deterministic world based on the laws of classic physics. However, the increased knowledge of relationships between metabolism, epigenetic systems, and editing of nucleic acids suggests the existence of self-organized processes of adaptive evolution in response to environmental stresses. Living organisms are open thermodynamic systems which use entropic decay of external source of electromagnetic energy to increase their internal dynamic order and to generate new genetic and epigenetic information with a high degree of coherency and teleonomic creativity. Sensing, information processing, and decision making of biological systems might be mainly quantum phenomena. Amplification of microscopic quantum events using the long-range correlation of fractal structures, at the borderline between deterministic order and unpredictable chaos, may be used to direct a reproducible transition of the biological systems towards a defined macroscopic state. The discoveries of many natural genetic engineering systems, the ability to choose the most effective solutions, and the emergence of complex forms of consciousness at different levels confirm the importance of mind-action directed processes in biological evolution, as suggested by Alfred Russel Wallace. Although the main Darwinian principles will remain a crucial component of our understanding of evolution, a radical rethinking of the conceptual structure of the neo-Darwinian theory is needed.

Natural selection is the ultimate, but not only force underlying organismal diversity. Despite this general biological insight, our understanding of how selection targets and shapes the genome during adaptation remains incomplete and is the central quest of this thesis. My main model organism is the threespine stickleback fish (Gasterosteus aculeatus). Stickleback provide an outstanding opportunity to study adaptive evolutionary change, because marine ancestors have repeatedly colonized and adapted to different freshwater environments all over the northern hemisphere since the last glacial retreat about 12,000 years ago. Besides wild populations, I also make use of lab-raised stickleback hybrids from controlled crosses for this thesis work. Thousands of genome-wide genetic polymorphisms (i.e., genetic markers) called in marine, but predominantly in distinct lake and stream stickleback populations from different geographic locations allow me to decipher the number and position of genomic targets of selection in the early phase of adaptive divergence. I find that selection acts on many loci distributed widely across the genome. On a genomic scale, the recombination landscape along chromosomes proves to be - in concert with selection - an important factor in driving heterogeneous genetic differentiation among populations. To investigate the rate of recombination across the stickleback's genome in more detail, I use an artificially crossed second-generation (F2) population. This reveals constraints in the frequency and location of detectable recombination events (i.e., cross-overs) within the genome. For example, cross-overs prove to be more frequent in chromosome peripheries than centers. This, together with selection, results in decreased within-population genetic diversity and increased between-population differentiation in the centers of chromosomes as opposed to the peripheries. Furthermore, I show that the cessation of recombination between the heterogametic sex chromosomes occurred in independent bouts. As a consequence, I find extended genomic regions distinct in their degree of degeneration between the X and Y chromosome, so called evolutionary strata. Finally, recombination reveals to be an important determinant of other aspects of a genome, such as its nucleotide composition. Integrating theoretical modeling with targeted and genome-wide sequencing, my research further demonstrates that the inference and interpretation of genomic regions exhibiting particularly high and low population differentiation is not as straightforward as commonly believed. This is because the type of genetic variation available to selection (i.e., pre-existing vs. de novo variation) as well as the mode of adaptation (i.e., divergent vs. parallel adaptation) influence the way neutral variation is shaped by selection across the genome. I demonstrate that a genomic region of high differentiation may not necessarily be indicative of divergent selection when populations adapt in parallel to similar environments from a shared pool of genetic variation. Based on several hundreds of F2 specimens reared under standardized conditions in the laboratory, I also link variation in heritable phenotypic traits to genetic variation, a research program generally referred to as quantitative trait locus (QTL) mapping. Corroborating with the results from my genome scans within and between wild populations (indicating that adaptive divergence involves many loci widespread across the genome), QTL mapping reveals that most phenotypic traits are controlled by numerous genetic loci. In general, each of these loci explains a small fraction of the entire phenotypic trait variation. I also use high resolution SNP data to infer the demographic history of several lake and stream stickleback populations from the Lake Constance watershed (Central Europe) and demonstrate that the repeated occurrence of similar stream phenotypes are, in this particular system, better explained by an evolutionary scenario of 'ecological vicariance' rather than repeated parallel divergence. I then show how selection has shaped local and broad-scale linkage, diversity and differentiation across the genome in these populations. Interestingly, I find evidence for strong divergent selection acting on large chromosomal rearrangements I had previously detected to be important for marine vs. freshwater adaptation. This finding provides a strong case for the re-use of pre-existing genetic variation in stickleback and demonstrates that the same genomic regions can be involved in adaptive divergence between disparate ecotype pairs. Overall, I come to conclude that signatures of selection are - at various physical scales - frequent within the stickleback genome. Stickleback repeatedly use pre-existing genetic variation, shared across various geographic ranges, to adapt to similar or disparate environments. Yet, there is a substantial degree of genetic non-parallelism - at least at the level of neutral markers - that goes along with parallel phenotypic evolution. My thesis emphasizes that the reliable detection and interpretation of genomic signatures of selection requires integrating many replicate study populations within a clear-cut ecological and demographic framework, as well as complementary analytical approaches. Controlled crossing experiments and theoretical modeling are key to deriving predictions about the genomics of adaptation in the wild and to facilitate our understanding of complex biological processes and patterns.

In Memoriam

Machinic Heterogenesis and Evolution

Evolution has endowed insects with an extraordinary capacity for miniaturization. Virtually all aspects of insect biology convey the sense of successfully uniting form and function in exquisitely small, diverse, and sophisticated motor, sensory, and metabolic systems (Grimaldi and Engel 2005). The ability of insects to fly in an efficient and controlled manner well illustrates how, through evolution by natural selection, they adapted to solve what we consider serious problems of engineering. Insects are little marvels of “evolutionary engineering.” The seemingly boundless ingenuity and creativity of the process of evolutionary adaptation are also reflected in the sensory systems of insects. As we try to make clear in this chapter, hearing in insects is a sophisticated process; understanding its fundamental mechanisms and trying to understand its evolution present many challenges but are likely to be very rewarding. Perhaps because insects are so small, their ears have generally been considered to be simple compared to those of vertebrates. Anatomically, they may be simpler, but their capacity for sound reception and processing turns out to be remarkably elaborate (for reviews, see Fullard and Yack 1993; Hoy 1998; Robert and Gopfert 2002; Robert 2005; Hedwig 2006; Gopfert and Robert 2007). The ears of insects can be as sensitive and acute as their vertebrate counterparts (Webster et al. 1992; Hoy 1998). Indeed, in some cases their feats of detection surpass the capabilities of vertebrates (Robert and Gopfert 2002). For example, the ultrafast ears of the parasitoid fly Ormia ochracea can distinguish time differences in the arrival...