Abstract
Quantitative linkages between individual organism movements and the resulting population distributions are fundamental to understanding a wide range of ecological processes, including rates of reproduction, consumption, and mortality, as well as the spread of diseases and invasions. Typically, quantitative data are collected on either movement behaviors or population distributions, rarely both. This study combines empirical observations and model simulations to gain a mechanistic understanding and predictive ability of the linkages between both individual movement behaviors and population distributions of a single-celled planktonic herbivore. In the laboratory, microscopic 3D movements and macroscopic population distributions were simultaneously quantified in a 1L tank, using automated video- and image-analysis routines. The vertical velocity component of cell movements was extracted from the empirical data and used to motivate a series of correlated random walk models that predicted population distributions. Validation of the model predictions with empirical data was essential to distinguish amongst a number of theoretically plausible model formulations. All model predictions captured the essence of the population redistribution (mean upward drift) but only models assuming long correlation times (minute), captured the variance in population distribution. Models assuming correlation times of 8 minutes predicted the least deviation from the empirical observations. Autocorrelation analysis of the empirical data failed to identify a de-correlation time in the up to 30-second-long swimming trajectories. These minute-scale estimates are considerably greater than previous estimates of second-scale correlation times. Considerable cell-to-cell variation and behavioral heterogeneity were critical to these results. Strongly correlated random walkers were predicted to have significantly greater dispersal distances and more rapid encounters with remote targets (e.g. resource patches, predators) than weakly correlated random walkers. The tendency to disperse rapidly in the absence of aggregative stimuli has important ramifications for the ecology and biogeography of planktonic organisms that perform this kind of random walk.
Highlights
Movement is fundamental to many ecological processes and often dictates relevant biotic and abiotic encounter rates, for planktonic organisms inhabiting a highly dynamic and heterogeneous habitat
Organism movement is fundamental to how organisms interact with each other and the environment
The empirical data are used to distinguish amongst a set of plausible theoretical modeling approaches to suggest that organism movements are highly correlated, meaning movement direction and speed is consistent over several minutes
Summary
Movement is fundamental to many ecological processes and often dictates relevant biotic and abiotic encounter rates, for planktonic organisms inhabiting a highly dynamic and heterogeneous habitat. Significant efforts have sought to establish mechanistic linkages between these individual movement behaviors and the resulting population distributions (reviewed in [5].) Deciphering these linkages for planktonic organisms, and others, provides powerful tools to predict rates of organism encounters with environmentally relevant factors and their ecological function. Founded on observations of the irregular motions of pollen, i.e. Brownian motion [6], random walk theory relates organism movements in terms of speed, direction or turning rate to probabilities of particle distribution [7,8,9]. Every formulation of a random walk model rests on a set of assumptions about the underlying movement parameters, their changes over time and dependence on internal or external stimuli [13]. As was recently shown for movement data of single-celled algae, widely used
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