Together with Éric Bapteste, Stefan Linquist, and W. Ford Doolittle, Nathalie Gontier was invited to participate in a double symposium session organized by François Papale and chaired by Philippe Huneman on Networks and the Ontology of Evolution for ISHPSSB 2019, the International Society for the History, Philosophy, and Social Studies of Biology.
Oslo, 11 July, 2019
Networks and the ontology of the theory of evolution by means of natural selection
Network-based models are at the forefront of contemporary research in evolutionary biology. Whether pictured in a diachronic or synchronic perspective, networks of interactions fashion biodiversity at all levels of organization. This has the potential of transforming our traditional understanding of the theory of evolution by means of natural selection. Given the rising interest in and the proliferation of network-based models, it is urgent for biology and the various disciplines studying it to evaluate the scientific changes this turn promises. This session aims at evaluating the consequences of this network-oriented tendency on the ontology of evolutionary biology. Since the advent of Modern Synthesis, evolutionary biology has been defined by its use of tree-based models of inheritance and phylogeny in the representation of evolutionary pattern. Traditionally, the use of tree-based models was justified by their success in ordering relationships among paradigmatic biological entities, namely genes and organisms, while the same tree-based models corroborated the relevance of those entities. From this justificatory structure followed constraints relative to the objects of inquiry: the processes that sustain branching patterns of divergence one side, the genealogical entities that populate these processes on the other. Conversely, a multitude of objects of inquiry have been under studied: among the neglected processes, we find hybridization, endosymbiosis, lateral gene transfer, regulation of gene expression, various developmental processes, symbiosis, convergent evolution, co-dependent and contingent evolution, etc.; among the neglected entities, we find communities of organisms, mobile genetic elements including transposable elements, ecosystems, memes or cultural units, multilevel systems, biochemical interaction systems involving genes and proteins, functional patterns (songs), etc. These objects have attracted more and more attention in the past decades, despite their friction with tree-based models. Network thinking provides a significantly different and more inclusive view of evolution and the relevant objects worth studying. Proponents of network-based approaches argue that: diachronically, representations of evolution are more accurate when they mobilize complex networks; synchronically, any time slice is best represented as a complex system of interactions; ontologically, biological entities are best conceived as nexuses generated by the coming together of various vectors of influence. If this approach prevails, the core principles of the theory of evolution by natural selection would have to be reinterpreted in a way that expands our understanding of the complexity of evolutionary phenomena. With network thinking, the variation that is the first matter upon which natural selection acts is to be seen as the result of complex interactions. The differential fitness between individuals is to be anchored in an ecological understanding of persistence and reproduction, while the patterns of inheritance are shown to go beyond mere vertical transmission. Given the importance of this potential transition from tree thinking to network-based approaches in evolutionary biology, there is a pressing need to start assessing its philosophical and scientific imports. This session focuses on one of the many aspects of the transition: how network analysis reshapes the ontology of evolutionary biology and what this entails for the theory of evolution by means of natural selection.
W. Ford Doolittle - to memes and back: ITSNTS theory and a deeper Darwinism
ITSNTS (“It’s The Song, Not The Singer”) theory was first formulated as an alternative to a popular view of “holobionts”, namely that collectives comprising microbial communities and their macrobial hosts form “units of selection” (Darwinian individuals in Godfrey-Smith’s sense). They generally do not, but one way to save the interest in such recurring interactions and account for the common observation that community (metabolic) “function” is more conserved than is community (taxonomic) composition is to see the interactions themselves as such a unit (1,2). Evolution by Natural Selection (ENS) is most often considered to entail the differential reproduction or replication of selected entities, criteria that holobionts do not often meet. But as Bouchard has argued (3), differential persistence can also underwrite it. ITSNTS theory offers a particular formulation of persistence selection in which processes (for example “holobiont” function, developmental interaction patterns, regulatory networks, biogeochemical cycles, community-level metabolism, ecosystem “functions” or cultural practices, all considered as “songs”) recruit (encourage the differential reproduction of) things (genes, taxa, cultural practitioners) that re-produce (produce again) or implement (“sing”) them. Songs persist, even though no parent-offspring lineages (essential in the accounting of differential reproduction) can be traced between their successive “singings”. Songs and singers make up interacting evolutionary domains, not nested levels in a hierarchy, and what looks like co-operation or inter- species altruism can be seen as selfish in both domains.
Stefan Linquist - A practical guide for universal Darwinism
When “Darwinian” thinking is extended to some novel domain – whether it is to transposons, cancer cells, or culture – the default tendency is to apply the principle of natural selection. This involves regarding the relevant entities as a phenotypically variable population, and searching for particular ecological factors that exert selection pressure on those variants. However, selectionist hypotheses are already difficult to test in conventional cases, i.e. using populations of familiar organisms in well understood ecological settings. This is why documented examples of natural selection are so rare. It is therefore impractical to begin with a selectionist framework when applying Darwinian thinking to novel domains, where the relevant entities or environments are often poorly understood. Alternatively, it makes more sense to begin with either a “purely ecological” or a “purely evolutionary” framework. The former ignores (for simplicity) phenotypic variation; the latter ignores particular features of the environment. One can then estimate the explanatory significance of each factor in isolation, before deciding whether it is practical to combine them. In this paper, I operationalize the “ecology versus evolution” distinction, and show how it is possible to estimate the influence of each type of factor in two unconventional cases: transposable elements and cultural replicators. This approach has at least one thing in common with network thinking. Ontological questions about the structure of the theory of natural selection, or about the necessary requirements for being “unit” of selection are intentionally downplayed. This is quite different from the approach taken, for example, by Dawkins in his discussion of memes. He began by asking, what does it take to be a unit of evolution? He then configured the idea of a meme around those requirements. Instead, I recommend beginning with some pattern in nature that calls for explanation, then building up to the question of whether natural selection can explain such patterns.
Nathalie Gontier - Beyond genealogy: How networks enable a modelling of the extended present
How we understand and depict information on the living and non-living world changes over time in association with varying cosmologies(1). Cosmologies are worldviews that provide theories on the nature of matter, space, and time, and these theories become depicted by cosmographies (2). Western cosmographies have transitioned from cyclic or circular wheels of time over static scales of nature to linear timelines that in turn have transformed into multilinear, bifurcating trees (3, 4, 6). Today, and throughout the sciences, tree models are being replaced by network diagrams. We will analyze how each of these iconic diagrams differentially depict hierarchical aspects of matter, space and time as well as how they are causally explained by different epistemologies. We will then hone in on network models that, in the evolutionary biological sciences in particular, have been introduced to portray aspects of reticulate evolution (5), but also gene-protein-cell interactions, and ecological relationships. Analyzing the power of networks, we will investigate how they enable a modelling of evolution in what can be called an extended present. Such goes beyond attempts to “merely” depict genealogical and historical relationships typical of phylogenetic and paleontological sciences (7), and we will examine how such calls out for ontological pluralism and a different conceptualization of both space and time.
Éric Bapteste - Turning evolutionary biology into a network science
Recent decades have seen the scientific understanding of biological complexity at various levels of organization (molecular, cellular and organismal) make a leap forward. Molecular interaction networks, lateral gene transfer, symbioses and endosymbioses are amongst the many drivers of biological evolution that, for billions of years, have led to the creation of multi lineages and multi-level collectives. The ubiquity of such collective organizations, usually represented by networks, is now widely recognized and accepted. Ipso facto, evolutionary biology, originally focused on tree like relationships, appears to be fundamentally turning into a science of dynamic networks. This state of affairs offers an original framework to unify, reconstruct and expend the theory of evolution. On the one hand, network-based analyses allow for a better specification of Lewontin’s three conditions of evolution by means of natural selection. On the other hand, this restructuration encourages a new multidisciplinary strategy to investigate evolution, that I call phylosystemics, which unites the short timescale of interactions studies from systems biologists and ecologists with the longer timescale of studies familiar to evolutionary biologists, by taking advantage of methods from network sciences.
François Papale - Redefining units of selections as networks of interactions: An ontological inquiry
The use of network-based models in evolutionary biology becomes more pervasive by the day. This methodological transition has important consequences, among which the need to review our ontological understanding of evolutionary individuals. In this presentation, I argue that individuals, in the context of Darwinian explanations, should be conceived as integrated networks of interactions to be described by their degree of integration. This view will be contrasted with Godfrey-Smith’s Darwinian individual framework (Godfrey-Smith 2009). Godfrey-Smith defines Darwinian individuals, the building blocks of Darwinian populations, as genealogical entities that can be isolated more or less straightforwardly. This means that a great diversity of entities and processes can be viewed as reproducers and reproduction, respectively: “That is fine, as long as we know who came from whom, and roughly where one begins and another ends.” (Godfrey-Smith 2009, 86). In order to provide finer grained descriptions of reproducers, Godfrey-Smith organizes them into three types: scaffolded, simple and collective. The distinction between single and collective reproducers on one side and scaffolded reproducers on the other is that the formers have “the machinery of reproduction internal to [them]” (Godfrey Smtih 2009, 88). The distinction between single reproducers and collective ones is that the latters are composed of lineages with evolutionary fates potentially independent from that of the whole. Network analyses of evolutionary dynamics provide a different picture of biological entities: those that do reproduce are phylogenetic mosaics composed of parts that have distinct evolutionary fates; moreover, their reproduction is made possible by complex networks of interactions involving entities at various levels of organization (Bapteste et Huneman 2018). At best, then, all reproducers could be described as scaffolded collectivities. However, even this readjustment is problematic. In the presentation, a network-based analysis of cases that are considered paradigmatic reproducers (genes, organisms like us, prokaryotic cells) will show that two out of the three criteria (bottleneck, germ line, integration) provided by Godfrey-Smith for describing collective reproducers are maladapted to a Darwinian perspective. Given these limitations, I argue for an alternative framework inspired by the work of various authors (Bouchard 2010; Brandon 1988; Dupré and O’Malley 2009; Millstein 2009): biological entities should be conceived as interactive networks whose degree of functional integration determines whether they can be considered units of selection or not. This degree can be assessed through rate of interactions within the studied biological object, whose boundaries can be drawn where the said rate drops significantly. This definition emphasizes that biological objects are collectivities and provides a more accurate reading of the part they play in evolutionary dynamics.
Copyright AppEEL 2012