Industrial bees: The impact of apicultural intensification on local disease prevalence
Industrial bees: The impact of apicultural intensification on local disease prevalence
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DOI：
10.1111/1365-2664.13461
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发表时间：
2019-07-16
影响因子：
5.7
通讯作者：
Boots, Michael
中科院分区：
文献类型：
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作者：
Bartlett, Lewis J.;Rozins, Carly;Boots, Michael
人们普遍认为，集约化耕作将导致更高的疾病发病率，尽管几乎没有具体的模型来检验这一观点。专注于蜜蜂，我们建立多群体模型，以告知如何“养蜂集约化”预测影响蜜蜂病原体流行病学在养蜂场规模。我们使用基于代理的模型和分析模型表明，养蜂集约化的三个相互关联的方面（人口规模的增加，人口网络结构的变化和群体间传播的增加）不太可能大大增加养蜂场的疾病流行率。这主要是因为即使是低强度的养蜂业也显示出高疾病流行率。养蜂集约化的影响最大的是R-0（基本繁殖数）相对较低的疾病，然而，这些疾病造成的总体疾病流行率很小，因此，集约化的影响是轻微的。此外，强化的影响最小的是具有高R-0值的疾病，我们认为这是典型的重要蜜蜂疾病。政策影响：我们的研究结果矛盾的想法，蜜蜂密集密集的养蜂场拥挤的蜂群，导致显着更高的疾病发病率为既定的蜜蜂病原体。更广泛地说，我们的工作表明，为了了解管理变化对疾病的影响，需要所有农业系统和管理实践的信息模型。
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.