Industrial bees: when agricultural intensification doesn't impact disease burden

10 Jul 2018, 11:10
New Law School/--028 (University of Sydney)

New Law School/--028

University of Sydney

Oral Presentation Ecology Social insects


Carly Rozins


The intensification of farming indisputably changes the ecology of agricultural infectious diseases with modern management practice impacting both host density and between-host contacts. We typically assert that these changes result in higher disease burdens, but there is relatively little specific modelling testing this idea. For example, the industrialisation of apiculture has been suggested to play a critical role in the increased losses of Apis mellifera colonies to infectious diseases, with specific apicultural practices (reflecting industry-wide intensification) implicated in higher disease burdens. Here we build multi- honeybee colony models to examine how ‘apicultural intensification’ in its most plausibly extreme case is predicted to impact honeybee pathogen epidemiology within apiary. Counter to the prevailing view, our models predict that intensification, captured though increased population sizes, changes in population network structure, and increased between-colony transmission, has little effect on disease burden across an apiary. Disease burdens, and therefore impacts of intensification, are critically determined by the R0 (reproductive ratio) of a given pathogen prior to intensification. The greatest impacts of intensification are found for diseases with initially low R0 values, however such diseases cause little overall disease burden and so impacts are universally minor. Importantly in this context, the smallest impacts of intensification are found for diseases with high R0 values, which appear to be typical of important honeybee diseases. Our findings highlight a lack of support for the hypothesis that current and ongoing aspects of management intensification lead to higher disease burdens in honeybees. More broadly, our work demonstrates the need for specific models of agricultural systems and management practices in order to understand the implications of management changes on disease burden.

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