The contextual approach is a prominent framework for thinking about group selection. Here, I highlight ambiguity about what the contextual approach is. Then, I discuss problematic entailments the contextual approach has for what processes count as group selection—entailments more troublesome than typically noted. However, Sober and Wilson’s version of the Price approach, which is the main alternative to the contextual approach, is problematic too: it leads to an underappreciated paradox called the vanishing selection problem and thereby generates the wrong qualitative (...) account of whether group selection is occurring in a certain family of cases. In response, I develop an account of group selection that can deal with the counterexamples to both the contextual approach and the Price approach. I then discuss the role that contextual analysis can continue to play in the discussion of individual fitness and metapopulation evolution. (shrink)

Evolution by natural selection has been extended to several supraorganismic levels, but whether it can apply to ecosystems remains controversial on two main counts. First, local ecosystems are loosely individuated, so that it is unclear how they manifest heredity and fitness. Second, even if they did, the meta-ecosystem formed by this population of local ecosystems will also suffer from a very low degree of cohesion, which will jeopardize any ENS. We suggest a way to overcome both issues, focusing on ecosystem (...) properties rather than on ecosystemic individuals. First, we follow recent theoretical developments which deny the centrality of reproduction in ENS. This leads us to merge heredity and fitness in a single process, in which a local ecosystem causally influences its neighbors, in a way responsible for their phenotypic similarity. Second, we suggest that the resulting meta-ecosystem need not meet the criteria of individuality. Instead, the evolving meta-ecosystem is best understood as a homeostatic property cluster, i.e., a set of phenotypes that together evolve by ENS at the ecosystem level. We illustrate this conceptual framework with a hypothetical example of local ecosystems that vary in terms of stability, productivity, diversity, and complementarity between species. Finally, we stress that our property-based account of ecosystemic ENS can help understand evolution at other biological levels, such as early life evolution and holobionts. (shrink)

Inclusive fitness theory provides conditions for the evolutionary success of a gene. These conditions ensure that the gene is selfish in the sense of Dawkins (The selfish gene, Oxford University Press, Oxford, 1976): genes do not and cannot sacrifice their own fitness on behalf of the reproductive population. Therefore, while natural selection explains the appearance of design in the living world (Dawkins in The blind watchmaker: why the evidence of evolution reveals a universe without design, W. W. Norton, New York, (...) 1996), inclusive fitness theory does not explain how. Indeed, Hamilton’s rule is equally compatible with the evolutionary success of prosocial altruistic genes and antisocial predatory genes, whereas only the former, which account for the appearance of design, predominate in successful organisms. Inclusive fitness theory, however, permits a formulation of the central problem of sociobiology in a particularly poignant form: how do interactions among loci induce utterly selfish genes to collaborate, or to predispose their carriers to collaborate, in promoting the fitness of their carriers? Inclusive fitness theory, because it abstracts from synergistic interactions among loci, does not answer this question. Fitness-enhancing collaboration among loci in the genome of a reproductive population requires suppressing alleles that decrease, and promoting alleles that increase the fitness of its carriers. Suppression and promotion are effected by regulatory networks of genes, each of which is itself utterly selfish. This implies that genes, and a fortiori individuals in a social species, do not maximize inclusive fitness but rather interact strategically in complex ways. It is the task of sociobiology to model these complex interactions. (shrink)