Resource landscapes and movement strategy shape Queensland Fruit Fly population dynamics
Animal population dynamics are shaped by their movement decisions in response to spatial and temporal resource availability across landscapes. The sporadic availability and diversity of resources can create highly dynamic systems. This is especially true in agro-ecological landscapes where the dynamic interplay of insect movement and heterogeneous landscapes hampers prediction of their spatio-temporal dynamics and population size.
We therefore systematically looked at population-level consequences of different movement strategies in temporally-dynamic resource landscapes for an insect species whose movement strategy is slightly understood: the Queensland Fruit Fly (Bactrocera tryoni)
We developed a spatially-explicit model to predict changes in population dynamics and sizes in response to varying resources across a landscape. We simulated the temporal dynamics of fruit trees as the main resource using empirical fruiting dates. Movement strategies were derived from general principles and varied in directedness of movement and movement trigger.
We showed that temporal continuity in resource availability was the main contributing factor for large and persistent populations. This explicitly included presence of continuous low-density resources such as fruit trees in urban areas. Analysing trapping data from SE Australia supported this finding. We also found strong effects of movement strategies, with directed movement supporting higher population densities.
These results give insight into structuring processes of spatial population dynamics of Queensland Fruit Fly in realistic and complex food production landscapes, but can also be extended to other systems. Such mechanistic understanding will help to improve forecasting of spatio-temporal hotspots and bottlenecks and will, in the end, enable more targeted population management.
KeywordsSpatially-explicit modelling Bactrocera tryoni Resource dynamics Spatio-temporal dynamics
The authors would like to thank Tony Clarke for his help on parameterizing the model with regards to QFly’s biology, and Penny Measham and several fruit-growers for a general information on host seasonality and their feedback on the model. Special thanks to Javier Navarro Garcia, Andrew Hulthen, and Justine Murray for providing the landuse data and helping with the respective analyses. Thanks to Justine Murray, Matt Hill, Marc Bélisle and one anonymous reviewer for helpful comments on earlier drafts of this manuscript. The “Adaptive Area Wide Management of Qfly using SIT” project is being delivered by Hort Innovation in partnership with CSIRO, and is supported by funding from the Australian Government Department of Agriculture & Water Resources as part of its Rural R&D for Profit program. Further partners include QUT, Agriculture Victoria, NSW DPI, PIRSA, SARDI, Wine Australia and BioFly.
FS, HP, and NS designed the study, FS did the modelling, analysed the results and wrote the first manuscript draft, all authors contributed significantly to subsequent versions of the manuscript. All authors have approved the final version of this article.
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