On the thermodynamics of multilevel evolution

Biodiversity is hierarchically structured both phylogenetically and functionally. Phylogenetic hierarchy is understood as a product of branching organic evolution as described by Darwin. Ecosystem biologists understand some aspects of functional hierarchy, such as food web architecture, as a product of evolutionary ecology; but functional hierarchy extends to much lower scales of organization than those studied by ecologists. We argue that the more general use of the term “evolution” employed by physicists and applied to non-living systems connects directly to the narrow biological meaning. Physical evolution is best understood as a thermodynamic phenomenon, and this perspective comfortably includes all of biological evolution. We suggest four dynamical factors that build on each other in a hierarchical fashion and set the stage for the Darwinian evolution of biological systems: (1) the entropic erosion of structure; (2) the construction of dissipative systems; (3) the reproduction of growing systems and (4) the historical memory accrued to populations of reproductive agents by the acquisition of hereditary mechanisms. A particular level of evolution can underpin the emergence of higher levels, but evolutionary processes persist at each level in the hierarchy. We also argue that particular evolutionary processes can occur at any level of the hierarchy where they are not obstructed by material constraints. This theoretical framework provides an extensive basis for understanding natural selection as a multilevel process. The extensive literature on thermodynamics in turn provides an important advantage to this perspective on the evolution of higher levels of organization, such as the evolution of altruism that can accompany the emergence of social organization.     

The evolution of eyes and visually guided behaviour

The morphology and molecular mechanisms of animal photoreceptor cells and eyes reveal a complex pattern of duplications and co-option of genetic modules, leading to a number of different light-sensitive systems that share many components, in which clear-cut homologies are rare. On the basis of molecular and morphological findings, I discuss the functional requirements for vision and how these have constrained the evolution of eyes. The fact that natural selection on eyes acts through the consequences of visually guided behaviour leads to a concept of task-punctuated evolution, where sensory systems evolve by a sequential acquisition of sensory tasks. I identify four key innovations that, one after the other, paved the way for the evolution of efficient eyes. These innovations are (i) efficient photopigments, (ii) directionality through screening pigment, (iii) photoreceptor membrane folding, and (iv) focusing optics. A corresponding evolutionary sequence is suggested, starting at non-directional monitoring of ambient luminance and leading to comparisons of luminances within a scene, first by a scanning mode and later by parallel spatial channels in imaging eyes.     

Predictive models in spatially and temporally variable freshwater systems

Abstract This paper discusses the relationships between scaling and predictability in ecosystems. The logical basis of ecosystem modelling is explored using ideas first developed in complexity theory and analogies with the behaviour of complex adaptive systems. Any ecological model is a scale-dependent entity and both empirical and dynamic models of freshwater systems have their strengths and weaknesses. The logical basis of modelling using functional groups is explored. I conclude that such an approach can be justified and that such models have predictive power. Any predictive model of freshwater systems must take the major scales of external (atmospheric and catchment) forcing into account as well as the scales of key processes in the ecosystem itself. The importance of so-called ‘pink noise’ spectra, which arise both from external forcing and the internal dynamics of dynamic systems, is noted. The key scales of pattern and process in freshwater ecosystems are discussed in relation to the properties of the major functional groups. In order to have predictive power, I conclude that models of freshwater systems must include sediment exchanges and the properties of aquatic macrophytes as well as water column interactions and the pelagic components. When viewed at the scale of functional groups and the major biogeochemical processes, freshwater ecosystems may not be as complex as is often assumed.     

Saltatory transitions are a naturally occurring property of evolving systems

On the basis of paleological evidence, it has been suggested that biological evolution need not necessarily be characterized by gradual change. Rather, evolutionary history may display saltatory periods of rapid speciation alternating with periods of relative quiescence, the whole dynamic being called punctuated equilibria. The empirical evidence that has been presented in support of this hypothesis has been the object of a vigorous dispute. Mathematical investigations of complex models of biological evolution that contain random elements have demonstrated that these systems can display saltatory behavior. In this paper we address a more abstract question: can saltations occur in the evolution of very simple, deterministic mathematical systems that function in a constant environment? The answer appears to be yes. Saltations appear as a natural dynamical behavior in the evolution of simplistic information processing networks. We stress that these networks do not constitute a model of biological evolution. However, the appearance of saltations in such simple systems suggests that their appearance in a process as complex as biological evolution is not surprising.     

Autonomy and hypersets

This paper has two primary aims. The first is to provide an introductory discussion of hyperset theory and its usefulness for modeling complex systems. The second aim is to provide a hyperset analysis of several perspectives on autonomy: Robert Rosen's metabolism-repair systems and his claim that living things are closed to efficient cause, Maturana and Varela's autopoietic systems, and Kauffman's cataytically closed systems. Consequences of the hyperset models for Rosen's claim that autonomous systems have non-computable models are discussed.     

Why a convincing argument for causalism cannot entirely eschew population-level properties: discussion of Otsuka

Causalism is the thesis that natural selection can cause evolution. A standard argument for causalism involves showing that a hypothetical intervention on some population-level property that is identified with natural selection (e.g., variation in fitness) will result in evolution. In a pair of articles, one of which recently appeared in the pages of this journal, Jun Otsuka has put forward a quite different argument for causalism. Otsuka attempts to show that natural selection can cause evolution by considering a hypothetical intervention on an individual-level property. Specifically, Otsuka identifies natural selection with the causal relationship between a trait and fitness, claims an intervention on the strength of this relationship can cause evolution, then concludes that natural selection can cause evolution. Below I describe why Otsuka’s argument for causalism is unconvincing. Central to my criticism is that Otsuka’s argument works only if one adopts an indefensible account of natural selection, according to which natural selection can occur in the absence of trait or fitness variation. I go on to explain why any attempt to demonstrate the truth of causalism via a hypothetical intervention on an individual-level property would appear to require one to adopt an account of natural selection that is inadequate for the same reason. This in turn means the plausibility of causalism does indeed depend on the plausibility of the claim that population-level properties, which supervene on the properties of the individuals in the population, can be causally efficacious.     

The Limitations of Kim’s Reductive Physicalism in Accounting for Living Systems and an Alternative Nonreductionist Ontology

Jaegwon Kim's exclusion argument is a general ontological argument, applicable to any properties deemed supervenient on a microproperty basis, including biological properties. It implies that the causal power of any higher-level property must be reducible to the subset of the causal powers of its lower-level properties. Moreover, as Kim's recent version of the argument indicates, a higher-level property can be causally efficient only to the extent of the efficiency of its micro-basis. In response, I argue that the ontology that aims to capture experimentally based explanations of metabolic control systems and morphogenetic systems must involve causally relevant contextual properties. Such an ontology challenges the exclusiveness of micro-based causal efficiency that grounds Kim's reductionism, since configurations themselves are inherently causally efficient constituents. I anticipate and respond to the reductionist's objection that the nonreductionist ontology's account of causes and inter-level causal relations is incoherent. I also argue that such an ontology is not open to Kim's overdetermination objection.     

When ABC becomes ACB

Understanding how the information contained in genes is mapped onto the phenotypes, and deriving formal frameworks to search for generic aspects of developmental constraints and evolution remains one of the main challenges of contemporary biological research. The Mexican endemic triurid Lacandonia schismatica (Lacandoniaceae), a mycoheterotrophic monocotyledonous plant with hermaphroditic reproductive axes is alone among 250,000 species of angiosperms, as it has central stamens surrounded by a peripheral gynoecium, representing a natural instance of a homeotic mutant. Based on the classical ABC model of flower development, it has recently been shown that the B-function gene APETALA3 (AP3), essential for stamen identity, was displaced toward the flower centre in L. schismatica (ABC to ACB) from the early stages of flower development. A functional conservation of B-function genes from L. schismatica through the rescue of B-gene mutants in Arabidopsis thaliana, as well as conserved protein interactions, has also been demonstrated. Thus, it has been shown that relatively simple genetic alterations may underlie large morphological shifts fixed in extant natural populations. Nevertheless, critical questions remain in order to have a full and sufficient explanation of the molecular genetic mechanisms underlying L. schismatica's unique floral arrangement. Evolutionary approaches to developmental mechanisms and systems biology, including high-throughput functional genomic studies and models of complex developmental gene regulatory networks, constitute two main approaches to meet such a challenge. In this review, the aim is to address some of the pending questions with the ultimate goal of investigating further the mechanisms of L. schismatica's unique homeotic flower arrangement and its evolution.     

Modeling in the museum: On the role of remnant models in the work of Joseph Grinnell

Accounts of the relation between theories and models in biology concentrate on mathematical models. In this paper I consider the dual role of models as representations of natural systems and as a material basis for theorizing. In order to explicate the dual role, I develop the concept of a remnant model, a material entity made from parts of the natural system(s) under study. I present a case study of an important but neglected naturalist, Joseph Grinnell, to illustrate the extent to which mundane practices in a museum setting constitute theorizing. I speculate that historical and sociological analyses of institutions can play a specific role in the philosophical analysis of model-building strategies.     

The evolution of vocabulary

Human language is unique among the communication systems of the natural world. The vocabulary of human language is unique in being both culturally transmitted and symbolic. In this paper I present an investigation into the factors involved in the evolution of such vocabulary systems. I investigate both the cultural evolution of vocabulary systems and the biological evolution of learning rules for vocabulary acquisition. Firstly, vocabularies are shown to evolve on a cultural time-scale so as to fit the expectations of learners-a population's vocabulary adapts to the biases of the learners in that population. A learning bias in favour of one-to-one mappings between meanings and words leads to the cultural evolution of communicatively optimal vocabulary systems, even in the absence of any explicit pressure for communication. Furthermore, the pressure to conform to the biases of learners is shown to outweigh natural selection acting on cultural transmission. Human language learners appear to bring a one-to-one bias to the acquisition of vocabulary systems. The functionality of human vocabulary may therefore be a consequence of the biases of human language learners. Secondly, the evolutionary stability of genetically transmitted vocabulary learning biases is investigated using both static and dynamic models. A one-to-one learning bias, which leads to the cultural evolution of optimal communication, is shown to be evolutionarily stable. However, the evolution de novo of this bias is complicated by the cumulative nature of the cultural evolution of vocabulary systems. This suggests that the biases of human language learners may not have evolved specifically and exclusively for the acquisition of communicatively functional vocabulary.     

Evolutionary consequences of selected locus-specific variations in epistasis and fitness contribution in Kauffman's NK model

Mathematical analysis and computer simulations are used to evaluate three modifications to Kauffman's NK model in an attempt to incorporate unexplored aspects of epistatic interaction between loci in genome evolution. Two modifications--one to the amount and the other to the distribution of epistatic interaction--further support Kauffman's conclusion that high levels of epistatic interaction lead to a decrease in overall fitness of the genome. The third model, however, provides a condition under which increased epistatic interaction at certain loci results in higher genome fitness.     

From survivors to replicators: evolution by natural selection revisited

For evolution by natural selection to occur it is classically admitted that the three ingredients of variation, difference in fitness and heredity are necessary and sufficient. In this paper, I show using simple individual-based models, that evolution by natural selection can occur in populations of entities in which neither heredity nor reproduction are present. Furthermore, I demonstrate by complexifying these models that both reproduction and heredity are predictable Darwinian products (i.e. complex adaptations) of populations initially lacking these two properties but in which new variation is introduced via mutations. Later on, I show that replicators are not necessary for evolution by natural selection, but rather the ultimate product of such processes of adaptation. Finally, I assess the value of these models in three relevant domains for Darwinian evolution.     

Self-organization and natural selection in the evolution of complex despotic societies

Differences between related species are usually explained as separate adaptations produced by individual selection. I discuss in this paper how related species, which differ in many respects, may evolve by a combination of individual selection, self-organization, and group-selection, requiring an evolutionary adaptation of only a single trait. In line with the supposed evolution of despotic species of macaques, we take as a starting point an ancestral species that is egalitarian and mildly aggressive. We suppose it to live in an environment with abundant food and we put the case that, if food becomes scarce and more clumped, natural selection at the level of the individual will favor individuals with a more intense aggression (implying, for instance, biting and fierce fighting). Using an individual-centered model, called DomWorld, I show what happens when the intensity of aggression increases. In DomWorld, group life is represented by artificial individuals that live in a homogeneous world. Individuals are extremely simple: all they do is flock together and, upon meeting one another, they may perform dominance interactions in which the effects of winning and losing are self-reinforcing. When the intensity of aggression in the model is increased, a complex feedback between the hierarchy and spatial structure results; via self-organization, this feedback causes the egalitarian society to change into a despotic one. The many differences between the two types of artificial society closely correspond to those between despotic and egalitarian macaques in the real world. Given that, in the model, the organization changes as a side effect of the change of one single trait proper to an egalitarian society, in the real world a despotic society may also have arisen as a side effect of the mutation of a single trait of an egalitarian species. If groups with different intensities of aggression evolve in this way, they will also have different gradients of hierarchy. When food is scarce, groups with the steepest hierarchy may have the best chance to survive, because at least a small number of individuals in such a group may succeed in producing offspring, whereas in egalitarian societies every individual is at risk of being insufficiently fed to reproduce. Therefore, intrademic group selection (selection within an interbreeding group) may have contributed to the evolution of despotic societies.     

The uniqueness of biological self-organization: challenging the Darwinian paradigm

Here we discuss the challenge posed by self-organization to the Darwinian conception of evolution. As we point out, natural selection can only be the major creative agency in evolution if all or most of the adaptive complexity manifest in living organisms is built up over many generations by the cumulative selection of naturally occurring small, random mutations or variants, i.e., additive, incremental steps over an extended period of time. Biological self-organization—witnessed classically in the folding of a protein, or in the formation of the cell membrane—is a fundamentally different means of generating complexity. We agree that self-organizing systems may be fine-tuned by selection and that self-organization may be therefore considered a complementary mechanism to natural selection as a causal agency in the evolution of life. But we argue that if self-organization proves to be a common mechanism for the generation of adaptive order from the molecular to the organismic level, then this will greatly undermine the Darwinian claim that natural selection is the major creative agency in evolution. We also point out that although complex self-organizing systems are easy to create in the electronic realm of cellular automata, to date translating in silico simulations into real material structures that self-organize into complex forms from local interactions between their constituents has not proved easy. This suggests that self-organizing systems analogous to those utilized by biological systems are at least rare and may indeed represent, as pre-Darwinists believed, a unique ascending hierarchy of natural forms. Such a unique adaptive hierarchy would pose another major challenge to the current Darwinian view of evolution, as it would mean the basic forms of life are necessary features of the order of nature and that the major pathways of evolution are determined by physical law, or more specifically by the self-organizing properties of biomatter, rather than natural selection.     

Evolutionary rescue beyond the models

Laboratory model systems and mathematical models have shed considerable light on the fundamental properties and processes of evolutionary rescue. But it remains to determine the extent to which these model-based findings can help biologists predict when evolution will fail or succeed in rescuing natural populations that are facing novel conditions that threaten their persistence. In this article, we present a prospectus for transferring our basic understanding of evolutionary rescue to wild and other non-laboratory populations. Current experimental and theoretical results emphasize how the interplay between inheritance processes and absolute fitness in changed environments drive population dynamics and determine prospects of extinction. We discuss the challenge of inferring these elements of the evolutionary rescue process in field and natural settings. Addressing this challenge will contribute to a more comprehensive understanding of population persistence that combines processes of evolutionary rescue with developmental and ecological mechanisms.     

Biodiversity is a chimera,and chimeras aren’t real

A recent article by Burch-Brown and Archer (Biol Philos, 2017) provides compelling arguments that biodiversity is either a natural kind or a pragmatically-valid scientific entity. I call into question three of these arguments. The first argument contends that biodiversity is a Homeostatic Property Cluster (HPC). I respond that there is no plausible homeostatic mechanism that would make biodiversity an HPC natural kind. The second argument proposes that biodiversity is a multiply-realizable functional kind. I respond that there is no shared function to ground this account. The final, and strongest, argument, is that biodiversity is an ineliminable explanans and explanandum in various subdisciplines of biology. I argue that once we look at the details of the relevant research, not only does biodiversity in a broad sense not function in explanatory roles, but we must eliminate biodiversity in favor of more specific concepts in order to make sense of the leading explanations in contemporary ecology and conservation science.     

The System of Interpretance, Naturalizing Meaning as Finality

A materialist construction of semiosis requires system embodiment at particular locales, in order to function as systems of interpretance. I propose that we can use a systemic model of scientific measurement to construct a systems view of semiosis. I further suggest that the categories required to understand that process can be used as templates when generalizing to biosemiosis and beyond. The viewpoint I advance here is that of natural philosophy—which, once granted, incurs no principled block to further generalization all the way to pansemiotics—nearer to Peirce’s own very general perspective. This project requires a hylozooic framework, which I present in the form of a specification hierarchy, whereby physical dynamics subsume all other transactions at more highly developed integrative levels. The upshot of the paper is a proposal that meanings can be assimilated most generally to final causes.     

A model for the evolutionary dynamics of cross-feeding polymorphisms in microorganisms

 Understanding mechanisms of evolutionary diversification is central to evolutionary biology. Microbes constitute promising model systems for observing processes of diversification directly in the laboratory. One of the main existing paradigms for microbial diversification is the evolution of cross-feeding polymorphisms, in which a strain specializing on a primary resource coexists with a cross-feeding strain that specializes on a waste product resulting from consumption of the primary resource. Here I propose a theoretical model for the evolutionary dynamics through which cross-feeding polymorphisms can gradually emerge from a single ancestral strain. The model is based on the framework of adaptive dynamics, which has proved to be very useful for studying adaptive processes of divergence under sympatric conditions. In particular, the phenomenon of evolutionary branching serves as a general paradigm for diversification. I show that evolutionary branching naturally occurs in evolutionary models of cross-feeding if (1) there is a trade-off between uptake efficiencies on the primary and secondary resources, and (2) this trade-off has positive curvature. The model also suggests that the evolution of cross-feeding should be more likely in chemostat cultures than in serial batch cultures, which conforms with empirical observations. Overall, the model provides a theoretical metaphor for the evolution of cross-feeding polymorphisms. Received: February 19, 2002 / Accepted: May 8, 2002     

Idealized, Inaccurate but Successful: A Pragmatic Approach to Evaluating Models in Theoretical Ecology

Ecologists attempt to understand the diversity of life with mathematical models. Often, mathematical models contain simplifying idealizations designed to cope with the blooming, buzzing confusion of the natural world. This strategy frequently issues in models whose predictions are inaccurate. Critics of theoretical ecology argue that only predictively accurate models are successful and contribute to the applied work of conservation biologists. Hence, they think that much of the mathematical work of ecologists is poor science. Against this view, I argue that model building is successful even when models are predictively inaccurate for at least three reasons: models allow scientists to explore the possible behaviors of ecological systems; models give scientists simplified means by which they can investigate more complex systems by determining how the more complex system deviates from the simpler model; and models give scientists conceptual frameworks through which they can conduct experiments and fieldwork. Critics often mistake the purposes of model building, and once we recognize this, we can see their complaints are unjustified. Even though models in ecology are not always accurate in their assumptions and predictions, they still contribute to successful science.