Rhythm and synchrony in animal movement and communication

Animal communication and motoric behavior develop over time. Often, this temporal dimension has communicative relevance and is organized according to structural patterns. In other words, time is a crucial dimension for rhythm and synchrony in animal movement and communication. Rhythm is defined as temporal structure at a second-millisecond time scale (Kotz et al. 2018). Synchrony is defined as precise co-occurrence of 2 behaviors in time (Ravignani 2017). Rhythm, synchrony, and other forms of temporal interaction are taking center stage in animal behavior and communication. Several critical questions include, among others: what species show which rhythmic predispositions? How does a species’ sensitivity for, or proclivity towards, rhythm arise? What are the species-specific functions of rhythm and synchrony, and are there functional trends across species? How did similar or different rhythmic behaviors evolved in different species? This Special Column aims at collecting and contrasting research from different species, perceptual modalities, and empirical methods. The focus is on timing, rhythm and synchrony in the second-millisecond range. Three main approaches are commonly adopted to study animal rhythms, with a focus on: 1) spontaneous individual rhythm production, 2) group rhythms, or 3) synchronization experiments. I concisely introduce them below (see also Kotz et al. 2018; Ravignani et al. 2018)

Animal Movement Strategies

Movement is a fundamental process in the natural world, and active movement in response to environmental drivers is key to animal ecology. The animal tracking revolution has led to at least two distinct challenges in the field of movement ecology. The first is how to gain ecologically meaningful insights into the proximate, mechanistic drivers of animal movement decisions from vast tracking datasets. The second is how to study their ultimate, evolutionary causes. In this PhD thesis, I attempt to tackle both challenges. In Part 1, I lay out a vision as well as guidelines for the processing of massive, high-throughput animal tracking datasets, which could enable the transition of movement ecology into a true ‘big data’ discipline. I demonstrate these methods and the mechanistic approach I advocate by studying the movement of moulting birds. Combining high-throughput tracking with viewsheds - what individuals can actually see from a location - I show that birds’ movement decisions are strongly influenced by whether potential destinations can be observed by predators. In Part 2, I propose a framework for conceptual insights into the evolution of animals’ movement decisions using individual-based models that include both ecological and evolutionary timescales. With one such model I show how animal movement and foraging competition decisions can evolve in tandem, and how ecological conditions can promote the rapid evolution of correlated suites of behaviours. With another similar model, I show how repeated pathogen spillovers into a population can drive the very rapid evolution of diverse social strategies. Finally, I show how individual-based models, in which all aspects of animals’ movement decision-making are known, can be useful conceptual tools to probe the performance of contemporary statistical methods in animal movement ecology

Suite of simple metrics reveals common movement syndromes across vertebrate taxa

ecause empirical studies of animal movement are most-often site- and species-specific, we lack understanding of the level of consistency in movement patterns across diverse taxa, as well as a framework for quantitatively classifying movement patterns. We aim to address this gap by determining the extent to which statistical signatures of animal movement patterns recur across ecological systems. We assessed a suite of movement metrics derived from GPS trajectories of thirteen marine and terrestrial vertebrate species spanning three taxonomic classes, orders of magnitude in body size, and modes of movement (swimming, flying, walking). Using these metrics, we performed a principal components analysis and cluster analysis to determine if individuals organized into statistically distinct clusters. Finally, to identify and interpret commonalities within clusters, we compared them to computer-simulated idealized movement syndromes representing suites of correlated movement traits observed across taxa (migration, nomadism, territoriality, and central place foraging)

Heart-rate pulse-shift detector

Detector circuit accurately separates and counts phase-shift pulses over wide range of basic pulse-rate frequency, and also provides reasonable representation of full repetitive EKG waveform. Single telemeter implanted in small animal monitors not only body temperature but also animal movement and heart rate