Longmuir, Daniel N.R., Hoskins, Andrew J., and Hickson, R.I. (2023) A metapopulation model of Little Red Flying Fox population dynamics across Queensland. In: Proceedings of the 25th International Congress on Modelling and Simulation. pp. 517-523. From: MODSIM 2023: 25th International Congress on Modelling and Simulation, 9-14 July 2023, Darwin, NT, Australia.

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Abstract

The Little Red Flying Fox (Pteropus scapulatus) is native to large coastal areas of northern and eastern Australia. A primary food source for this species is the nectar from Eucalyptus and Corymbia blossoms. There is only partial understanding of their roosting locations (known as “camps”) and movement, being semi-nomadic in nature to move between flowering events and camps. This creates a complexity in modelling the Little Red Flying Fox population. However, through stacked data including monthly spatial estimates of nectar availability, we can begin to understand how the bats move with these events. To investigate the population dynamics, we use a metapopulation model, coupling the spatial data of average monthly nectar availability through a radiation model for movement between camps. We couple the approximately 1 × 1km spatial nectar data using Voronoi diagrams based on known camp locations. The radiation model then considers a combination of camp distance and nectar availability to determine which patch leaving bats move to. We use a combination of density and caloric needs approach to limit the population in a patch. We compare our modelled population with historic camp survey data of population estimates. We show this relatively simple metapopulation model results in emergent behaviour aligned with the observation of ecologists, particularly to do with movement and patch numbers around pupping season. We showcase two areas of interest, regions across Cape Yorke and around Brisbane, where seasonal trends are expected to be substantially different. This metapopulation model based on nectar availability will form the basis of further work exploring infectious diseases risks, such as Hendra or Leptospirosis. Our model can be extended to consider the spatio-temporal availability of other resources, such as fresh water, vegetation coverage, and other environmental factors (temperature, humidity, aridity, etc.).

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