Show simple item record

dc.contributor.authorGiles, John R
dc.contributor.authorPlowright, Raina K
dc.contributor.authorEby, Peggy
dc.contributor.authorPeel, Alison J
dc.contributor.authorMcCallum, Hamish
dc.date.accessioned2018-01-11T00:44:42Z
dc.date.available2018-01-11T00:44:42Z
dc.date.issued2016
dc.identifier.issn2045-7758
dc.identifier.doi10.1002/ece3.2382
dc.identifier.urihttp://hdl.handle.net/10072/100471
dc.description.abstractFruit bats (Pteropodidae) have received increased attention after the recent emergence of notable viral pathogens of bat origin. Their vagility hinders data collection on abundance and distribution, which constrains modeling efforts and our understanding of bat ecology, viral dynamics, and spillover. We addressed this knowledge gap with models and data on the occurrence and abundance of nectarivorous fruit bat populations at 3 day roosts in southeast Queensland. We used environmental drivers of nectar production as predictors and explored relationships between bat abundance and virus spillover. Specifically, we developed several novel modeling tools motivated by complexities of fruit bat foraging ecology, including: (1) a dataset of spatial variables comprising Eucalypt-focused vegetation indices, cumulative precipitation, and temperature anomaly; (2) an algorithm that associated bat population response with spatial covariates in a spatially and temporally relevant way given our current understanding of bat foraging behavior; and (3) a thorough statistical learning approach to finding optimal covariate combinations. We identified covariates that classify fruit bat occupancy at each of our three study roosts with 86–93% accuracy. Negative binomial models explained 43–53% of the variation in observed abundance across roosts. Our models suggest that spatiotemporal heterogeneity in Eucalypt-based food resources could drive at least 50% of bat population behavior at the landscape scale. We found that 13 spillover events were observed within the foraging range of our study roosts, and they occurred during times when models predicted low population abundance. Our results suggest that, in southeast Queensland, spillover may not be driven by large aggregations of fruit bats attracted by nectar-based resources, but rather by behavior of smaller resident subpopulations. Our models and data integrated remote sensing and statistical learning to make inferences on bat ecology and disease dynamics. This work provides a foundation for further studies on landscape-scale population movement and spatiotemporal disease dynamics.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherJohn Wiley & Sons
dc.relation.ispartofpagefrom7230
dc.relation.ispartofpageto7245
dc.relation.ispartofissue20
dc.relation.ispartofjournalEcology and Evolution
dc.relation.ispartofvolume6
dc.subject.fieldofresearchLandscape ecology
dc.subject.fieldofresearchEcology
dc.subject.fieldofresearchEvolutionary biology
dc.subject.fieldofresearchEcological applications
dc.subject.fieldofresearchcode410206
dc.subject.fieldofresearchcode3103
dc.subject.fieldofresearchcode3104
dc.subject.fieldofresearchcode4102
dc.titleModels of Eucalypt phenology predict bat population flux
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
dcterms.licensehttp://creativecommons.org/licenses/by/4.0/
dc.description.versionVersion of Record (VoR)
gro.facultyGriffith Sciences, Griffith School of Environment
gro.rights.copyright© 2016 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
gro.hasfulltextFull Text
gro.griffith.authorMcCallum, Hamish
gro.griffith.authorPeel, Alison J.


Files in this item

This item appears in the following Collection(s)

  • Journal articles
    Contains articles published by Griffith authors in scholarly journals.

Show simple item record