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Industrial bees: The impact of apicultural intensification on local disease prevalence
Author(s) -
Bartlett Lewis J.,
Rozins Carly,
Brosi Berry J.,
Delaplane Keith S.,
Roode Jacobus C.,
White Andrew,
Wilfert Lena,
Boots Michael
Publication year - 2019
Publication title -
journal of applied ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.503
H-Index - 181
eISSN - 1365-2664
pISSN - 0021-8901
DOI - 10.1111/1365-2664.13461
Subject(s) - apiary , beekeeping , population , disease , biology , agriculture , ecology , environmental health , medicine , pathology
It is generally thought that the intensification of farming will result in higher disease prevalences, although there is little specific modelling testing this idea. Focussing on honeybees, we build multi‐colony models to inform how “apicultural intensification” is predicted to impact honeybee pathogen epidemiology at the apiary scale. We used both agent‐based and analytical models to show that three linked aspects of apicultural intensification (increased population sizes, changes in population network structure and increased between‐colony transmission) are unlikely to greatly increase disease prevalence in apiaries. Principally this is because even low‐intensity apiculture exhibits high disease prevalence. The greatest impacts of apicultural intensification are found for diseases with relatively low R 0 (basic reproduction number), however, such diseases cause little overall disease prevalence and, therefore, the impacts of intensification are minor. Furthermore, the smallest impacts of intensification are for diseases with high R 0 values, which we argue are typical of important honeybee diseases. Policy Implications: Our findings contradict the idea that apicultural intensification by crowding honeybee colonies in large, dense apiaries leads to notably higher disease prevalences for established honeybee pathogens. More broadly, our work demonstrates the need for informative models of all agricultural systems and management practices in order to understand the implications of management changes on diseases.