Do species factories exist? Detecting exceptional patterns of evolution in the mammalian fossil record

A species factory refers to the source that gives rise to an exceptionally large number of species. However, what is it exactly: a place, a time or a combination of places, times and environmental conditions, remains unclear. Here we search for species factories computationally, for which we develop statistical approaches to detect origination, extinction and sorting hotspots in space and time in the fossil record. Using data on European Late Cenozoic mammals, we analyse where, how and how often species factories occur, and how they potentially relate to the dynamics of environmental conditions. We find that in the Early Miocene origination hotspots tend to be located in areas with relatively low estimated net primary productivity. Our pilot study shows that species first occurring in origination hotspots tend to have a longer average longevity and a larger geographical range than other species, thus emphasizing the evolutionary importance of the species factories.Peer reviewe

Modelling recurrent events for improving online change detection

The task of online change point detection in sensor data streams is often complicated due to presence of noise that can be mistaken for real changes and therefore affecting performance of change detectors. Most of the existing change detection methods assume that changes are independent from each other and occur at random in time. In this paper we study how performance of detectors can be improved in case of recurrent changes. We analytically demonstrate under which conditions and for how long recurrence information is useful for improving the detection accuracy. We propose a simple computationally efficient message passing procedure for calculating a predictive probability distribution of change occurrence in the future. We demonstrate two straightforward ways to apply the proposed procedure to existing change detection algorithms. Our experimental analysis illustrates the effectiveness of these approaches in improving the performance of a baseline online change detector by incorporating recurrence information. Read More: http://epubs.siam.org/doi/10.1137/1.9781611974348.6