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Counterintuitive scaling between population size and density: implications for modelling transmission of infectious diseases in bat populations
  • +4
  • Tamika Lunn,
  • Alison J Peel,
  • Peggy Eby,
  • Remy Brooks,
  • Raina K Plowright,
  • Maureen K Kessler,
  • Hamish Mccallum
Tamika Lunn
Environmental Futures Research Institute, Griffith University
Author Profile
Alison J Peel
Environmental Futures Research Institute, Griffith University
Peggy Eby
School of Biological Earth and Environmental Sciences, University of New South Wales, Environmental Futures Research Institute, Griffith University
Remy Brooks
Environmental Futures Research Institute, Griffith University
Raina K Plowright
Department of Microbiology and Immunology, Montana State University
Maureen K Kessler
Department of Ecology, Montana State University
Hamish Mccallum
Environmental Futures Research Institute, Griffith University

Abstract

  1. Models of host-pathogen interactions help to explain infection dynamics in wildlife populations and to predict and mitigate the risk of zoonotic spillover. Insights from models inherently depend on the way contacts between hosts are modelled, and crucially, how transmission scales with animal density.
  2. Bats are important reservoirs of zoonotic disease and are among the most gregarious of all mammals. Their population structures can be highly heterogenous, underpinned by ecological processes across different scales, complicating assumptions regarding the nature of density-transmission scaling. Although models commonly parameterise transmission using metrics of total abundance, whether this is an ecologically representative approximation of host-pathogen interactions is not routinely evaluated.
  3. We collected a 13-month dataset of roosting Pteropus spp. from 2,522 spatially referenced trees across eight roosts to compare density estimates across scales (roost-level, subplot-level, tree-level). We then focus on tree-level measures of abundance and density, the scale most likely to be relevant for virus transmission between tree-roosting Pteropus , and evaluate whether roost features at different scales are predictive of local dynamics.
  4. Our density estimates varied greatly by scale. Mean density ofPteropus at the roost level was 13-fold lower than at a subplot-level that accounted for heterogenous distributions of bats (0.38 bats/m2 vs 5.13 bats/m2). Additionally, roost-level measures (roost abundance and roost area) did not represent tree-level abundance or tree-level density, with models explaining minimal variation in tree-level measures.
  5. This indicates that basic measures, such as roost-level population counts, may not provide adequate approximations for population dynamics at scales relevant for transmission, and that alternative measures are needed to compare transmission potential between roosts. From the best candidate models, the best predictor of local population structure was tree density within roosts, where roosts with low tree density had a higher abundance but lower density of bats (more spacing between bats) per tree.
  6. Together, these data highlight unpredictable and counterintuitive relationships between abundance and density, and between measures at different scales. More nuanced modelling of transmission, spread and spillover from bats likely requires alternative approaches to integrating contact structure in host-pathogen models, rather than simply modifying the transmission function.