Population structure attributable to reproductive time: isolation by time and adaptation by time

Many populations are composed of a mixture of individuals that reproduce at different times, and these times are often heritable. Under these conditions, gene flow should be limited between early and late reproducers, even within populations having a unimodal temporal distribution of reproductive activity. This temporal restriction on gene flow might be called "isolation by time" (IBT) to acknowledge its analogy with isolation by distance (IBD). IBD and IBT are not exactly equivalent, however, owing to differences between dispersal in space and dispersal in time. We review empirical studies of natural populations that provide evidence for IBT based on heritabilities of reproductive time and on molecular genetic differences associated with reproductive time. When IBT is present, variation in selection through the reproductive season may lead to adaptive temporal variation in phenotypic traits [adaptation by time (ABT)]. We introduce a novel theoretical model that shows how ABT increases as (i) selection on the trait increases; (ii) environmental influences on reproductive time decrease; (iii) the heritability of reproductive time increases; and (iv) the temporal distribution of reproductive activity becomes increasingly uniform. We then review empirical studies of natural populations that provide evidence for ABT by documenting adaptive temporal clines in phenotypic traits. The best evidence for IBT and ABT currently comes from salmonid fishes and flowering plants, but we expect that future work will show these processes are more widespread.     

Memory time

In this issue of Neuron, MacDonald et al. describe hippocampal "time cells" that fire during specific delay periods as rats performed a memory task. Converging results in monkeys suggest that the hippocampus encodes episodes by signaling events in time.     

Mapping time

Neuronal coding of temporal stimulus features can occur by means of delay lines. Given that neuronal activity is conducted through many parallel axons, there has to be a mechanism guaranteeing minimal temporal dispersion. We argue that plastic changes in synaptic transmission that are unspecifically propagated along presynaptic axons are a basis for the development of delay-line topologies. Furthermore, we show how two populations of afferents form a map of interaural time differences as found, for instance, in the laminar nucleus of the barn owl.     

Our time,their time,world time: The transformation of temporal modes*

This article discusses Protestant movements in a village in the Peruvian Andes. It tries to explain why villagers either reject or are attracted to Protestantism. The argument is that explanations traditionally proposed by anthropologists fail to account for the segmentation into competing denominations, the problem of relapse to Catholicism, and second‐ and third‐time conversion, and that new approaches are required to understand the nature of contemporary Protestant movements in Latin America. The article concludes that we enlarge our framework to include urban migrants and focus on the ties which link these migrants to their native village.     

Mean residence time in multicompartmental models with time delays

Calculation of the mean residence time (MRT) of a drug in a stationary compartmental model is classically carried out from several expressions. Nevertheless, one or more time delays between compartments modify the mean residence times. It is the aim of this paper to propose a general method for MRT calculations, in any n-compartmental models which may include time delays. As examples, catenary and mammillary models are considered.     

Aligning gene expression time series with time warping algorithms

motivation: Increasingly, biological processes are being studied through time series of RNA expression data collected for large numbers of genes. Because common processes may unfold at varying rates in different experiments or individuals, methods are needed that will allow corresponding expression states in different time series to be mapped to one another. Results: We present implementations of time warping algorithms applicable to RNA and protein expression data and demonstrate their application to published yeast RNA expression time series. Programs executing two warping algorithms are described, a simple warping algorithm and an interpolative algorithm, along with programs that generate graphics that visually present alignment information. We show time warping to be superior to simple clustering at mapping corresponding time states. We document the impact of statistical measurement noise and sample size on the quality of time alignments, and present issues related to statistical assessment of alignment quality through alignment scores. We also discuss directions for algorithm improvement including development of multiple time series alignments and possible applications to causality searches and non-temporal processes ('concentration warping').