Adaptive diversification in heterogeneous environments

Discovery of widely available abyssal rock patches reveals overlooked habitat type and prompts rethinking deep-sea biodiversity

Ground-truthed analyses of multibeam sonar data along a fracture zone of the northern Mid-Atlantic Ridge reveal an abyssal seafloor much rockier than previously assumed. Our data show rock exposures occurring at all crustal ages from 0–100 Ma along the Vema Fracture Zone and that approximately 260,000 km² of rock habitats can be expected to occur along Atlantic fracture zones alone. This higher than expected geodiversity implies that future sampling campaigns should be considerably more sophisticated than at present to capture the full deep-sea habitat heterogeneity. We provide a baseline to unravel the processes responsible for the evolution and persistence of biodiversity on the deep seafloor as well as to determine the significant scales of these processes in the benthoscape.

Habitat heterogeneity and species diversity are often linked. On the deep seafloor, sediment variability and hard-substrate availability influence geographic patterns of species richness and turnover. The assumption of a generally homogeneous, sedimented abyssal seafloor is at odds with the fact that the faunal diversity in some abyssal regions exceeds that of shallow-water environments. Here we show, using a ground-truthed analysis of multibeam sonar data, that the deep seafloor may be much rockier than previously assumed. A combination of bathymetry data, ruggedness, and backscatter from a trans-Atlantic corridor along the Vema Fracture Zone, covering crustal ages from 0 to 100 Ma, show rock exposures occurring at all crustal ages. Extrapolating to the whole Atlantic, over 260,000 km² of rock habitats potentially occur along Atlantic fracture zones alone, significantly increasing our knowledge about abyssal habitat heterogeneity. This implies that sampling campaigns need to be considerably more sophisticated than at present to capture the full deep-sea habitat heterogeneity and biodiversity.

Bayesian inference of natural selection from spatiotemporal phenotypic data

Spatiotemporal variations of natural selection may influence the evolution of various features of organisms such as local adaptation or specialisation. This article develops a method for inferring how selection varies between locations and between generations from phenotypic data. It is assumed that generations are non-overlapping and that individuals reproduce by selfing or asexually. A quantitative genetics model taking account of the effects of stabilising natural selection, the environment and mutation on phenotypic means and variances is developed. Explicit results on the evolution of populations are derived and used to develop a Bayesian inference method. The latter is applied to simulated data and to data from a wheat participatory plant breeding programme. It has some ability to infer evolutionary parameters, but estimates may be sensitive to prior distributions, for example when phenotypic time series are short and when environmental effects are large. In such cases, sensitivity to prior distributions may be reported or more data may be collected.