The intra- and interspecific facets of biodiversity have traditionally been quantified and analysed separately, limiting our understanding of how evolution has shaped biodiversity, how biodiversity (as a whole) alters ecological dynamics, and hence eco-evolutionary feedbacks at the community scale. Here, we propose using candidate genes phylogenetically-conserved across species and sustaining functional traits as an inclusive biodiversity unit transcending the intra- and interspecific boundaries. This framework merges knowledge from functional genomics and functional ecology, and we first provide conceptual and technical guidelines for identifying phylogenetically-conserved candidate genes (PCCGs) within communities, and for measuring inclusive biodiversity from PCCGs. We then explain how biodiversity measured at PCCGs can be linked to ecosystem functions, which may unify recent observations that both intra- and interspecific biodiversity are important for ecosystem functions. We then highlight the eco-evolutionary processes shaping PCCGs diversity patterns, and argue that their respective role can be inferred from concepts derived from population genetics. Finally, we explain how PCCGs may shift the field of eco-evolutionary dynamics from a focal-species approach to a more realistic focal-community approach. This framework provides a novel perspective to investigate the global ecosystem consequences of diversity loss across biological scales, and how these ecological changes further alter biodiversity evolution.

Recent studies have highlighted associations between diseases and host microbiota. However, the role of microbe in infection process is yet to be clarified between host microbiota promoting future infections, or changes in host microbiota resulting from infections. We longitudinally surveyed, in the wild, the microbiota of individual fish hosts (Leuciscus burdigalensis) both before and after infection by a crustacean ectoparasite (Tracheliastes polycolpus). We found a striking association between parasite infection and the host microbiota composition restricted to the fins the parasite anchored. We clearly demonstrated that infections by the parasite induced a shift in (and did not result from) the host fin microbiota. Fin microbiota further got similar to that of the adult stage, and the free-living infective stage of the parasite during infection with a predominance of the Burkholderiaceae bacteria family. This suggests that Burkholderiaceae bacteria is involved in a co-infection process and possibly facilitate T. polycolpus infection.

Invasive species are significant contributors to global changes and constitute a severe threat to biodiversity. Yet invasions offer an incredible framework to understand how small and low-diverse introduced populations adapt to novel environmental conditions and succeed in colonizing large areas. However, due to the insufficient data on the origin of the first introduced propagule and the first stage of invasion, reconstructing a species’ invasion history is challenging. Here, we applied genetic clustering methods and explicit admixture tests combined with ABC models and Machine Learning algorithms to describe the phylogeography of native and invasive populations and infer the most probable demographic invasion scenarios of Pseudorasbora parva, a highly invasive freshwater fish and the healthy carrier of a novel lethal fungi-like pathogen (Sphaerothecum destruens), which is responsible for the decline of several fish species in Europe. We found that the current genetic structuring of the native P. parva range has been shaped by waves of gene flow originating from southern and northern Chinese populations. Furthermore, our results strongly suggest that the invasive genetic diversity is the outcome of past recurrent global invasion pathways of admixed native populations. Our study also illustrates how the combination of admixture tests, ABC, Machine Learning can be used to detect high-resolution demographic signatures and reconstruct an integrative biological invasion history.