AMoveE 2014: Sharon Bewick
Channel: Movebank
Date: 2014-05-20

This talk was presented by Sharon Bewick on 7 May 2014 as part of the Symposium on Animal Movement and the Environment, held at the North Carolina Museum of Natural Sciences in Raleigh.

Bewick S, Krotkov T, Varassin IG, Fagan WF, 2014, "Understanding pollinator foraging strategies in terms of dynamic resource landscapes"

Abstract: Dynamic resource landscapes can strongly influence how individual movement behaviors give rise to population-level distributions. Here we seek to understand how the foraging behavior of pollinators, which has implications for both plant and pollinator fitness, gives rise to patterns of space use by pollinators. To explore the mechanistic underpinnings of different foraging strategies, we build an individual-based neural network genetic algorithm (ING) model to describe pollinator movement through a 1D field of flowers. Within our formulation, context-specific state variables representing a pollinator's environment are converted to movement responses using an artificial neural network (ANN). The ANN itself then evolves according to a genetic algorithm. Using our model, we investigate the different types of foraging behaviors that emerge as a function of resource characteristics across the landscape. We consider, for example, flower density, flower patchiness, nectar replenishment rates, flower rewards, variability in nectar replenishment rates and variability in flower rewards. In addition, we consider several pollinator life-history traits, for example competition effects and the capacity for memory. Ultimately, our model allows us to define the types of plant and pollinator characteristics that give rise to different types of pollinator foraging strategies, ranging from restricted foraging that frequents a small number of patches to long-distance trap-lines with and without returns.