Macroevolutionary patterns in the diversification of parrots: effects of climate change, geological events and key innovations

Aim Parrots are thought to have originated on Gondwana during the Cretaceous. The initial split within crown group parrots separated the New Zealand taxa from the remaining extant species and was considered to coincide with the separation of New Zealand from Gondwana 82-85 Ma, assuming that the diversification of parrots was mainly shaped by vicariance. However, the distribution patterns of several extant parrot groups cannot be explained without invoking transoceanic dispersal, challenging this assumption. Here, we present a temporal and spatial framework for the diversification of parrots using external avian fossils as calibration points in order to evaluate the relative importance of the influences of past climate change, plate tectonics and ecological opportunity. Location Australasian, African, Indo-Malayan and Neotropical regions. Methods Phylogenetic relationships were investigated using partial sequences of the nuclear genes c-mos, RAG-1 and Zenk of 75 parrot and 21 other avian taxa. Divergence dates and confidence intervals were estimated using a Bayesian relaxed molecular clock approach. Biogeographic patterns were evaluated taking temporal connectivity between areas into account. We tested whether diversification remained constant over time and if some parrot groups were more species-rich than expected given their age. Results Crown group diversification of parrots started only about 58 Ma, in the Palaeogene, significantly later than previously thought. The Australasian lories and possibly also the Neotropical Arini were found to be unexpectedly species-rich. Diversification rates probably increased around the Eocene/Oligocene boundary and in the middle Miocene, during two periods of major global climatic aberrations characterized by global cooling. Main conclusions The diversification of parrots was shaped by climatic and geological events as well as by key innovations. Initial vicariance events caused by continental break-up were followed by transoceanic dispersal and local radiations. Habitat shifts caused by climate change and mountain orogenesis may have acted as a catalyst to the diversification by providing new ecological opportunities and challenges as well as by causing isolation as a result of habitat fragmentation. The lories constitute the only highly nectarivorous parrot clade, and their diet shift, associated with morphological innovation, may have acted as an evolutionary key innovation, allowing them to explore underutilized niches and promoting their diversification.

Simultaneous Multiscale Polyaffine Registration by Incorporating Deformation Statistics

Locally affine (polyaffine) image registration methods capture intersubject non-linear deformations with a low number of parameters, while providing an intuitive interpretation for clinicians. Considering the mandible bone, anatomical shape differences can be found at different scales, e.g. left or right side, teeth, etc. Classically, sequential coarse to fine registration are used to handle multiscale deformations, instead we propose a simultaneous optimization of all scales. To avoid local minima we incorporate a prior on the polyaffine transformations. This kind of groupwise registration approach is natural in a polyaffine context, if we assume one configuration of regions that describes an entire group of images, with varying transformations for each region. In this paper, we reformulate polyaffine deformations in a generative statistical model, which enables us to incorporate deformation statistics as a prior in a Bayesian setting. We find optimal transformations by optimizing the maximum a posteriori probability. We assume that the polyaffine transformations follow a normal distribution with mean and concentration matrix. Parameters of the prior are estimated from an initial coarse to fine registration. Knowing the region structure, we develop a blockwise pseudoinverse to obtain the concentration matrix. To our knowledge, we are the first to introduce simultaneous multiscale optimization through groupwise polyaffine registration. We show results on 42 mandible CT images.