Adaptive evolution across multi-scale biological systems: finding a bridge between molecular evolution and multi-species dynamics.

Genes exist within species, species exist within communities, and communities exist within ecosystems. Consider the emergent complexity of a multi-species community; it is a self-organizing system shaped by the combined activities of its species, with the information required for those activities stored at "lower levels" within genes. The biological activities occurring inside of the species, or the community, can manifest externally (e.g., changing the ecosystem), and thereby influence the properties and dynamics of the community itself. The key insight here is that the fitness landscape that genes "perceive" cannot be independent of how those genes affect higher levels of complexity. Therefore a complex biological system (e.g., a community) can develop a complex network of causal interactions over evolutionary time, with feedback between levels (e.g., genes, species and community) influencing each gene's adaptive landscape. However, the classical account of adaptive gene evolution, as embodied by neo-Darwinian theory, is reductionist and largely assumes unidirectional causal pathways. Thus, the classical approach has struggled to provide a full account of how evolution can establish and fine-tune links within multi-scale biological systems. Such multi-level causality motivated the highly-regarded philosopher of biology, Evelyn Fox Keller, to question the way biologists use the concept of "the gene for." to explain complex biological systems. If Evelyn Fox Keller is correct, then fundamental questions about the origin and evolution of complexity cannot be solved if we persist in pursuing purely reductive explanations. Indeed, Keller has recently called on biologists to adapt their analysis and modelling techniques to address multi-scale systems, and to consider a "pluralistic mosaic" of different strategies. The proposed research program is a response to Keller's call from my perspective as an evolutionary biologist. Fundamental questions about biological complexity, such as those surrounding adaptive evolution across multi-scale systems, have fallen through the cracks of investigation because they lie on the boundary of two or more fields. The traditional approach to adaptive gene evolution is firmly rooted in population genetic theory and, while necessary, its scope is limited by a highly reductive view of adaptive landscapes. A complete understanding of adaptive evolution will require us to consider (i) the effect of multi-scale dynamics (e.g., multi-gene and multi-species interactions) on adaptive landscapes, (ii) a de-centralized mapping of genotype and phenotype, and (iii) multiple fields of biology. Because we are asking new questions, we will need to develop new research tools. Hence, this project seeks to develop theory and methods appropriate for understanding adaptive dynamics of genes (and genomes) across multi-scale biological systems. Trainees will acquire data science and genomics skills suitable to a broad the range of careers.