The tree, the network, and the species

To enrich the Hennigian internodal conception of species, a new formalization of the definition of the species concept is proposed. This rigorous definition allows for considerable unification of the various, and sometimes conflicting, techniques of species delimitation used in practice. First, the domain of such a definition is set out, namely, the set of all organisms on Earth, past, present, and future. Next, the focus is on the genealogical relationship among organisms, which provides the key to analysing the giant or global genealogical network (GGN) connecting all these organisms. This leads to the construction of an algorithm revealing the topological structure of the GGN, from families to lineages, ending up with a definition of species as equivalence classes of organisms corresponding to branches of the 'tree of life'. Such a theoretical definition of the species concept must be accompanied by various recognition criteria to be operational. These criteria are, for example, the ill-named 'biological species concepts', 'phylogenetic species concepts', etc., usually, but wrongly, presented as definitions of the species concept. Besides clarifying this disputed point, the definition in the present study displays the huge diversity of the scales (time-scale and population size) involved in actual species, thus explaining away the classical problems raised by previous attempts at defining the species concept (uniparental reproduction, temporal depth of species, and hybridization).  © 2006 The Linnean Society of London, Biological Journal of the Linnean Society , 2006, 89 , 509–521.     

Darwin,the amphibians,and the natural selection

A critical review of Darwin's publications shows that he did not dissert much about amphibians, in comparison with the other tetrapods. However, in “A Naturalist's Voyage round the World”, Darwin described for the first time several amphibian species and was surprised by their peculiar way of life, terrestrial or euryhaline. These amphibian observations around the world led Darwin to discuss evolutionnary notions, like developmental heterochronies or evolving convergences, and later to illustrate his famous natural selection theory. This is confirmed, for example, by the publication of “On the Origin of Species” where Darwin ironically questioned creation theory, trying to explain the absence of amphibians on oceanic islands. Lamarck also considered amphibians as relevant material to illustrate his theory of acquired character heredity. These historical uses of lissamphibians as evolutionary models have been mostly realized before any amphibian fossil discovery, i.e. out of a palaeontological context.     

Causality, randomness, intelligibility, and the epistemology of the cell

Because the basic unit of biology is the cell, biological knowledge is rooted in the epistemology of the cell, and because life is the salient characteristic of the cell, its epistemology must be centered on its livingness, not its constituent components. The organization and regulation of these components in the pursuit of life constitute the fundamental nature of the cell. Thus, regulation sits at the heart of biological knowledge of the cell and the extraordinary complexity of this regulation conditions the kind of knowledge that can be obtained, in particular, the representation and intelligibility of that knowledge. This paper is essentially split into two parts. The first part discusses the inadequacy of everyday intelligibility and intuition in science and the consequent need for scientific theories to be expressed mathematically without appeal to commonsense categories of understanding, such as causality. Having set the backdrop, the second part addresses biological knowledge. It briefly reviews modern scientific epistemology from a general perspective and then turns to the epistemology of the cell. In analogy with a multi-faceted factory, the cell utilizes a highly parallel distributed control system to maintain its organization and regulate its dynamical operation in the face of both internal and external changes. Hence, scientific knowledge is constituted by the mathematics of stochastic dynamical systems, which model the overall relational structure of the cell and how these structures evolve over time, stochasticity being a consequence of the need to ignore a large number of factors while modeling relatively few in an extremely complex environment.