V. Life's Corporeal Evolution Develops, Encodes and Organizes Itself: An Earthtwinian Genesis Synthesis

Lewitus, Eric and Helene Morlon. Natural Constraints to Species Diversification. PLoS Biology. Online August, 2016. As the extended Abstract explains, École Normale Supérieure, Paris, biologists employ the latest analytic and geometric measures to discern the presence of inherent universal principles and patterns that are found to array across and distinguish life’s long developmental ascent to our worldwide ability to discover this.

Identifying modes of species diversification is fundamental to our understanding of how biodiversity changes over evolutionary time. Diversification modes are captured in species phylogenies, but characterizing the landscape of diversification has been limited by the analytical tools available for directly comparing phylogenetic trees of groups of organisms. Here, we use a novel, non-parametric approach and 214 family-level phylogenies of vertebrates representing over 500 million years of evolution to identify major diversification modes, to characterize phylogenetic space, and to evaluate the bounds and central tendencies of species diversification. We identify five principal patterns of diversification to which all vertebrate families hold. These patterns, mapped onto multidimensional space, constitute a phylogenetic space with distinct properties.

Firstly, phylogenetic space occupies only a portion of all possible tree space, showing family-level phylogenies to be constrained to a limited range of diversification patterns. Secondly, the geometry of phylogenetic space is delimited by quantifiable trade-offs in tree size and the heterogeneity and stem-to-tip distribution of branching events. Finally, both the constrained range and geometry of phylogenetic space are established by the differential effects of macroevolutionary processes on patterns of diversification. Given these properties, we show that the average path through phylogenetic space over evolutionary time traverses several diversification stages, each of which is defined by a different principal pattern of diversification and directed by a different macroevolutionary process. The identification of universal patterns and natural constraints to diversification provides a foundation for understanding the deep-time evolution of biodiversity. (Abstract)

Lipson, Hod, et al. On the Origin of Modular Variation. Evolution. 56/8, 2002. Computer simulations reveal why functional modules inherently form and evolve.

Lister, Adrian. Behavioural Leads in Evolution: Evidence from the Fossil Record. Biological Journal of the Linnean Society. Online October, 2013. A senior Natural History Museum, London, zoologist marshals copious evidence to claim that across the Metazoan kingdoms, creatures engage in proactive conduct to survive, reproduce and prevail, which then drives and influences life’s evolutionary trajectory.

There has been much discussion of the role of behaviour in evolution, especially its potential to lead morphological evolution by placing the organism in a novel selective environment. Many adaptations of living species can be imagined to have originated in this way, although documented examples are relatively few. A fruitful arena for testing hypotheses about behavioural innovation is the fossil record. Traditionally, the behaviour of fossil species has been deduced from their morphology, precluding the observation of a behavioural lead preceding morphological evolution. This circularity can be broken by examining behavioural proxies independent of the adaptive morphology itself. Examples applicable to fossil remains include dietary information (e.g. wear traces on teeth, stable isotopes) and trace fossils indicating locomotor mode (footprints). The signature of a behavioural lead would be an observed shift in behaviour from one horizon (or taxon) to another, followed later by a functionally-related morphological change.

This pattern can be sought either in finely-stratified anagenetic sequences of fossils (stratophenetic approach) or among fossils with well-resolved species-level phylogenies (cladistic approach). An array of case studies from the literature is presented. These include feeding shifts in finely-resolved sequences of vertebrates ranging from freshwater fish to terrestrial ungulates, as well as locomotor changes crucial to major evolutionary transitions in the origin of tetrapods, birds, and humans. The latter examples highlight the role of behaviour in initiating exaptation (the requisitioning of structure for a new function). The case studies also illustrate the challenges of using fossil sequences to elucidate behavioural roles, including insufficient stratigraphic resolution and uncertainty over the adaptive function of observed traits. By the same token, they suggest criteria for choosing promising cases for research, as well as for formulating testable hypotheses about evolutionary modes. (Abstract)

Livnat, Adi. Interaction-Based Evolution: How Natural Selection and Nonrandom Mutation Work Together. Biology Direct. Online October, 2013. In a 43 page essay, a Virginia Tech assistant professor of biological sciences with a 2006 doctorate in Ecology and Evolutionary Biology from Princeton University delves into a revisionary expansion of the Modern Synthesis. This online journal edited by Eugene Koonin, Laura Landweber and David Lipman provides articles with peer reviews, in this case Nigel Goldenfeld, Jurgen Brosius, and Ford Doolittle. As the quotes convey, the composite posting could exemplify the state of evolutionary theory. At the outset Livnat feels obligated to say that his approach is “mechanistic” in kind, and will not detract from natural selection as the lone operative. As other works at this frontier, he then proceeds to do the opposite. While not Lamarckian, epigenetic influences are quite in effect beyond the molecular genome. Further novel aspects are broached but it is averred they do not carry any sense of teleology. Conversations with Gunter Wagner, Simon Levin, Marc Feldman, others, are acknowledged, and affinities with the work of James Shapiro, Lynn Caporale and Arlin Stoltzfus (search), so his views are representative. Goldenfeld found the article “provocative and stimulating,” and to Brosius it was “eye-opening,” but Doolittle was “very irritated.” To wit while some “nonrandom, non-accidental” stimulus does seem at work, selection will not to be parted with until this evident prior agency can be fully explained by a robust, understandable theory. And a tacit impediment remains an alien physical cosmos sans any enlivening, generative program of its own.

Here I address these questions from a unified perspective, by means of a new mechanistic view of evolution that offers a novel connection between selection on the phenotype and genetic evolutionary change (while relying, like the traditional theory, on natural selection as the only source of feedback on the fit between an organism and its environment). I hypothesize that the mutation that is of relevance for the evolution of complex adaptation—while not Lamarckian, or “directed” to increase fitness—is not random, but is instead the outcome of a complex and continually evolving biological process that combines information from multiple loci into one. This allows selection on a fleeting combination of interacting alleles at different loci to have a hereditary effect according to the combination’s fitness. (Hypothesis)

My general approach will be as follows. I will continue to assume that selection is the only source of feedback on the fit between an organism and its environment. However, I will revisit the question of the nature of the mutation that drives evolution. Here, I will continue to assume that mutation is not Lamarckian, and that a given mutation is not more likely to occur in an environment where it increases fitness than in an environment where it does not. However, I will show that there is another alternative, which has not been attended to yet, which is neither accidental mutation nor mutation that violates our core assumptions. Revisiting the question of the nature of mutation, I will construct a new theory of how adaptive evolution happens, based on selection, but also on a new connection between selection on the phenotype and genetic evolutionary change. I will show that this approach addresses the unresolved problems of sex and interactions from a unifying perspective, and at the same time begins to propose a mechanism at the point where traditional theory relies only on pure chance. (4)

This paper holds that the mutation that drives evolution is not a result of random accident but an outcome of a mutational writing phenotype. This phenotype itself evolves, like anything else inherent to the organism. It absorbs the information that comes from selection and guides selection further by providing further variation. (38) The process described here is “Kantian” in that it shows that evolution is driven not only by external forces. It is not random accident that generates the variance that selection operates on. Rather, a phenotype causing syntactic internal change is absorbing information from the outside world—from natural selection—and changes itself in the process. (39)

Livnat, Adi. Simplification, Innateness, and the Absorption of Meaning from Context. Evolutionary Biology. Online March, 2017. The University of Haifa theorist continues his project (search) to achieve a better explanation of life’s evolution as due in some way to algorithmic computations, network propensities, genome – language affinities, neural net deep learning, and more. By enlisting these current insights, an advance beyond Darwinian natural selection as the only agency is proposed so as to identify and explain an actual non-random or non-accidental innate essence. We quote at length to convey the substantial contribution. An earlier posting is available at arXiv:1605.03440.

Considering all the above, we can now describe a main point of this paper. Evolution is a bottomless system. One cannot define all words in the dictionary in terms of other words without getting into a circularity. Ultimately, the meaning of words comes from the context of their usage; that is how language is learned and even how it evolves. The genes are similar in this regard. Their meaning comes from their context of usage. They themselves are nodes in a network, in development as well as in evolution. The upshot of this is that the bottom of the hierarchy of biological interactions - the genetic sequence - is not a stable ground upward of which life is built. Mutation is not a local accident that brings innovation all on its own as though there is no living network that it needs to connect to. The process of genetic change is a complex one where the connections between nodes in the network become stronger and weaker as they form modules that absorb meaning from context. (9)

4.15 The Engine of Evolution Interaction-based evolution argues that the process whereby a population converges on an adaptation is a process that converts information from a less orderly to a more orderly state. It proceeds from a fuzzy to a sharp, well-working and stereotyped state. However, evolution is not only a fuzzy-to-sharp process, in that the fuzzy source must first arise. The progress from fuzzy to sharp is therefore only a half of a cycle of the “engine of creativity" that is evolution. The other half is that previously made sharp elements come together at a high level to make the new fuzzy source from which new sharp elements can be made. I argued that simplification under performance pressure connects the two parts of the cycle. The simple elements it creates not only are improvements but also come together in new complex interactions which serve as the raw material for the next round of simplification. Thus, novelty arises not from accident, but from evolutionary work. (29)

Furthermore, the fact that the output of a mutational event at one generation, namely the mutation itself, can serve as an input into mutational events at later generations means that the mutation-writing phenotype creates a network of information flow through the generations, from many genes into any one gene and from any one gene to many. Other examples of networks of information flow and computation include the brain, and what computer scientists call a circuit (one instance of which is an artificial neural network). Thus, according to interaction-based evolution, genetic evolution can be seen as the result of the workings of a network, itself evolving over time. (37)

The philosophical move that is required from the perspective of interaction-based evolution is to let go of the notion that random mutation and novelty from a point are at the bottom of things - that they provide a stable ground upward from which a conceptual edifice can be built; and to accept instead that the action is at the network level: that both the meaning and origin of genetic and phenotypic elements comes from the higher levels of organization - it comes from the network - from above. This move opens up the study of evolution substantially; because while the notion of random mutation means that there is nothing of importance to be studied about the causes of mutation from an evolutionary perspective, the concept of non-accidental mutation provided by interaction-based evolution implies instead a whole world of biological mechanisms open to investigation. (38-40)

Lobkovsky, Alexander, et al. Predictability of Evolutionary Trajectories in Fitness Landscapes. PLoS Computational Biology. 7/12, 2011. National Center for Biotechnology Information, NIH, systems biologists including Yuri Wolf, and Eugene Koonin, provide, among a growing chorus, one more entry into and evidence via protein gyrations of a nascent genesis synthesis beyond random, aimless selection, whereby life’s emergent development is indeed found to track a repeatable, oriented pathway.

Is evolution deterministic, hence predictable, or stochastic, that is unpredictable? What would happen if one could ‘‘replay the tape of evolution’’: will the outcomes of evolution be completely different or is evolution so constrained that history will be repeated? Arguably, these questions are among the most intriguing and most difficult in evolutionary biology. In other words, the predictability of evolution depends on the fraction of the trajectories on fitness landscapes that are accessible for evolutionary exploration. Because direct experimental investigation of fitness landscapes is technically challenging, the available studies only explore a minuscule portion of the landscape for individual enzymes. We therefore sought to investigate the topography of fitness landscapes within the framework of a previously developed model of protein folding and evolution where fitness is equated with robustness to misfolding. We show that model-derived and experimental landscapes are significantly smoother than random landscapes and resemble moderately perturbed additive landscapes; thus, these landscapes are substantially robust to mutation. The model landscapes show a deficit of suboptimal peaks even compared with noisy additive landscapes with similar overall roughness. Thus, the smoothness and substantial deficit of peaks in fitness landscapes of protein evolution could be fundamental consequences of the physics of protein folding. (2)

Lobskovsky, Alexander and Eugene Koonin. Replaying the Tape of Life: Quantification of the Predictability of Evolution. Frontiers in Bioinformatics and Computational Biology. 3/Article 246, 2012. Some two decades ago Stephen Jay Gould claimed that if earth life evolved again, since by his ken no innate guidance or direction exists, human-like beings would not appear. Here National Center for Biotechnology Information systems biologists with vastly more evidence to drawn upon beg to differ. As others have voiced, (search Fontana for example) convergent constraints and other organizing forces now understood would still channel life’s emergence toward nested, complexity and intelligence.

All these caveats notwithstanding, recent experimental and model studies make it abundantly clear that short-term evolution in a fixed environment is far more predictable in a quantitative sense measured by the path divergence than it would be in an uncorrelated landscape. In other words, although multiple evolutionary trajectories are often accessible, evolution is strongly constrained and the part of the fitness landscape available for exploration is highly variable but typically small. Thus, if we actually could replay the tape of evolution, the outcome could have been considerably more similar to the existing diversity of life forms than Gould expected. (6)

Losos, Jonathan. Improbable Destinies: How Predictable is Evolution? New York: Penquin, 2017. A Harvard University, Organismic and Evolutionary Biology professor alludes that while evolutionary developments do converge upon similar forms, a constant, quirky contingency which causes life to ever splay into arbitrary directions seems to rule. While local pathways may be followed, an overall drive and direction and aim does not exist, we are a lucky fluke.

Love, Alan, ed. Conceptual Change in Biology: Scientific and Philosophical Perspectives on Evolution and Development. Dordrecht: Springer, 2015. Select papers from a 2010 Dahlem Workshop held at the MPI for History of Science, Berlin, as a 30 year retrospect after a 1981 meeting that began explorations of an Evo-Devo unification. Topics such as adaptation, allometry, heterochrony, homoplasy, plasticity, constraint, hierarchies, are discussed by leading researchers David Wake, Fred Nijhout, Marc Kirschner, Rudolf Raff, Gunter Wagner, Wallace Arthur, Stuart Newman and more. But the focus seemed to be more on conceptual theories rather than an inquiry upon what life’s long phylogeny is doing and becoming by its own innate propensities.

Lu, Qiaoying and Pierrick Bourrat. The Evolutionary Gene and the Extended Evolutionary Synthesis. British Journal for the Philosophy of Science. Online June, 2017. Macquarie University and University of Sydney philosophers of biology consider how such revisions are influenced by on-going malleable definitions of what this nucleotide molecule actually is and does. Along with the quotes, see also, e.g., The Human Microbiome and the Missing Heritability Problem by Santiago Sandoval-Motta, et al (2017 search).

Advocates of an ‘extended evolutionary synthesis’ have claimed that standard evolutionary theory fails to accommodate epigenetic inheritance. The opponents of the extended synthesis argue that the evidence for epigenetic inheritance causing adaptive evolution in nature is insufficient. We suggest that the ambiguity surrounding the conception of the gene represents a background semantic issue in the debate. Starting from Haig’s gene-selectionist framework and Griffiths and Neumann-Held’s notion of the evolutionary gene, we define senses of ‘gene’, ‘environment’, and ‘phenotype’ in a way that makes them consistent with gene-centric evolutionary theory. We argue that the evolutionary gene, when being materialized, need not be restricted to nucleic acids but can encompass other heritable units such as epialleles. If the evolutionary gene is understood more broadly, and the notions of environment and phenotype are defined accordingly, current evolutionary theory does not require a major conceptual change in order to incorporate the mechanisms of epigenetic inheritance. (Abstract)
Epiallele and Epigene: An epiallele is one of a number of alternative difference makers, such as alternative epigenetic modifications, that cause epigenetic inheritance. The set of epialleles that leads to the same phenotypic difference (at a given grain of description) represents an epigene. (4)

Even if the term ‘gene’ comes to be used to refer to the molecular gene exclusively, and theorists employ another term (such as ‘replicator’) when referring to our concept of evolutionary gene, the conceptual analysis we provide will still be valuable insofar as it highlights two things: First researchers should define the concepts they use and carefully interpret works from different fields; this is crucial for productive interdisciplinary discussion. Second, the discovery of DNA as the material basis for genetic information, understood in the evolutionary sense, does not mean that it is the only basis for it. Hence, we are confident that current evolutionary theory is resilient and adaptive enough to incorporate new hereditary materials without requiring profound conceptual changes. (20-21)

Mabee, Paula. Integrating Evolution and Development: The Need for Bioinformatics in Evo-Devo. BioScience. 56/4, 2006. An overview of this historic reintegration of genotype and phenotype, known as evolutionary developmental biology, which studies transformations in morphology over time. In this regard, a major aspect is a pervasive modularity in genetic, embryonic, and evolutionary domains, for …modules are the units of evolution. A systems or network understanding can be further facilitated by computer ontologies, along with improved visualization methods. If a tendency to form pattern and process modules is so constant, and since complex adaptive self-organization is known to generate nested modular structures and entities, one then wonders such presence in life’s progression could be attributed to an independent, universal source.

MacIver, Malcolm and Barbara Finlay. The neuroecology of the water-to-land transition and the evolution of the vertebrate brain. Philosophical Transactions of the Royal Society B. December, 2021. Veteran Northwestern University and Cornell University evolutionary neuroscientists make a case that this epochal movement of aquatic creatures onto dry, sunlit surfaces played a much more paramount role in life’s emergence than previously seen.

The water-to-land transition in vertebrate evolution offers a unique opportunity for computational affordances and a new ecology for the brain. As a result, a much enlarged visual sensorium owing to air versus water as a medium, then led to mobile eyes and neck. In water, the midbrain tectum coordinates approach/avoid decisions, due to water flow and the bodily state and learning. On land, the relative motions of sensory surfaces and effectors must be resolved, adding on computational architectures from the dorsal pallium. For the large-brained and long-living denizens, making the right decision allows animals to learn from experience. Integration of memorized panoramas in the basal ganglia/frontal cortex becomes a substantial cognitive habit-to-plan benefit. (Excerpt)

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