Accurate forecasts of how animals respond to climate-driven environmental change are needed prepare for future redistributions, however, it is unclear which temporal scales variability give rise predictability species distributions. We examined the that best predicted spatial abundance a marine predator, swordfish Xiphias gladius, in California Current. To understand provide biological predicta...

During online speech processing, our brain tracks the acoustic fluctuations in speech at different timescales. Previous research has focused on generic timescales (for example, delta or theta bands) that are assumed to map onto linguistic features such as prosody or syllables. However, given the high intersubject variability in speaking patterns, such a generic association between the timescale...

Studies of connectivity of natural populations are often conducted at different timescales. Studies that focus on contemporary timescales ask questions about dispersal abilities and dispersal behavior of their study species. In contrast, studies conducted at historical timescales are usually more focused on evolutionary or biogeographic questions. In this paper we present a synthesis of connect...

Although neuronal excitability is well understood and accurately modeled over timescales of up to hundreds of milliseconds, it is currently unclear whether extrapolating from this limited duration to longer behaviorally relevant timescales is appropriate. Here we used an extracellular recording and stimulation paradigm that extends the duration of single-neuron electrophysiological experiments,...

Scale separation crossing many orders of magnitude is a consistent challenge in the ecological sciences. Wind dispersal of seed that generates plant propagation fronts is a typical case where timescales range from less than a second for fast turbulent processes to interannual timescales governing plant growth and climatic forcing. We show that the scale separation can be overcome by developing ...

This paper proposes a novel graphical method (3D-LD) based on wavelets for studying scaling and non-stationary signals. We show that it allows to better study the timescale-dependent qualitative properties of such signals, compared to the classical techniques. By using the 3D-LD, we study two recent network traffic traces to understand the actual nature of scaling in TCP flow arrivals. We show ...