Memories of Migrations Past: Sociality and Cognition in Dynamic, Seasonal Environments

Eliezer Gurarie,Sriya Potluri,Robert Stephen Cantrell,William F Fagan,George Christopher Cosner

doi:10.3389/fevo.2021.742920

Abstract

Seasonal migrations are a widespread and broadly successful strategy for animals to exploit periodic and localized resources over large spatial scales. It remains an open and largely case-specific question whether long-distance migrations are resilient to environmental disruptions. High levels of mobility suggest an ability to shift ranges that can confer resilience. On the other hand, a conservative, hard-wired commitment to a risky behavior can be costly if conditions change. Mechanisms that contribute to migration include identification and responsiveness to resources, sociality, and cognitive processes such as spatial memory and learning. Our goal was to explore the extent to which these factors interact not only to maintain a migratory behavior but also to provide resilience against environmental changes. We develop a diffusion-advection model of animal movement in which an endogenous migratory behavior is modified by recent experiences via a memory process, and animals have a social swarming-like behavior over a range of spatial scales. We found that this relatively simple framework was able to adapt to a stable, seasonal resource dynamic under a broad range of parameter values. Furthermore, the model was able to acquire an adaptive migration behavior with time. However, the resilience of the process depended on all the parameters under consideration, with many complex trade-offs. For example, the spatial scale of sociality needed to be large enough to capture changes in the resource, but not so large that the acquired collective information was overly diluted. A long-term reference memory was important for hedging against a highly stochastic process, but a higher weighting of more recent memory was needed for adapting to directional changes in resource phenology. Our model provides a general and versatile framework for exploring the interaction of memory, movement, social and resource dynamics, even as environmental conditions globally are undergoing rapid change.

Highlights

Seasonal migrations are widespread among terrestrial, aquatic, avian and invertebrate species (Dingle, 2014)
Our goal was to develop a minimal heuristic in which the following processes were explicitly modeled: (1) Random or exploratory movement, (2) attraction to resources, (3) sociality in the movements, (4) a long-term memory of large-scale movement behavior, and (5) a short-term memory that updates movement behavior based on recent experience
We explored this model using numerical differencing of a system of ordinary differential equations (ODE’s) approximating the partial differential equations (PDEs) in Equation (1) with the Runge-Kutte algorithm using the deSolve (Soetaert et al, 2010) and ReacTran (Soetaert and Meysman, 2012) packages in R

Summary

Introduction

Seasonal migrations are widespread among terrestrial, aquatic, avian and invertebrate species (Dingle, 2014). Some migrants follow a “green wave” of spring vegetation as it flowers across altitudinal or latitudinal gradients (Bischof et al, 2012; Kölzsch et al, 2015; Merkle et al, 2016). These migrations can be considered “tactical,” as they can occur—as an extreme simplification—purely as response to local conditions. Other migrants perform long-distance migrations in anticipation that critical resources will be available at the time of arrival at the end point of migration (Abrahms et al, 2019) This second behavior involves the greatest trade-off between the costs and benefits of accessing those highly seasonal and localized resources. This approach can be considered “strategic” in the sense that it is driven not by immediate cues but by an anticipation based on prior experience (Bracis and Mueller, 2017; Merkle et al, 2019; Bauer et al, 2020)

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Conclusion