Quantifying inherent predictability and spatial synchrony in the aphid vector Myzus persicae: field-scale patterns of abundance and regional forecasting error in the UK.
Quantifying inherent predictability and spatial synchrony in the aphid vector Myzus persicae: field-scale patterns of abundance and regional forecasting error in the UK.
复制标题
量化蚜虫媒介桃蚜的固有可预测性和空间同步性：英国的田间规模丰度模式和区域预测误差。
DOI：
10.1002/ps.7292
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发表时间：
2023
影响因子：
4.1
通讯作者：
Bell JR
中科院分区：
文献类型：
--
作者：
Bell JR
甜菜受到病毒黄化的威胁，这是一种由蚜虫传播的疾病，会降低糖含量。我们提出了一个分析桃蚜种群动态与无烟碱类种子处理。我们使用了6年的黄色水陷阱和田间收集的蚜虫数据以及20年的12.2 m吸捕器蚜虫迁移数据。我们调查的空间同步性和预测误差，了解结构和空间尺度的字段计数和为什么预测蚜虫移民缺乏准确性。我们的目的是获得统计参数，通知区域范围内的害虫管理strategies.ResultsSpatial synchronization，表示随着时间的推移，在整个地区的计数的一致变化，是很少存在的，最好描述为随机。独特的是，2019年的早季田间种群确实显示出90公里的空间同步性，而整体平均每周相关长度为23公里。然而，70%的时间序列在空间上是异质的，这表明场间动力学是不均匀的。现场计数缺乏相同的季节性趋势，并没有在同一周达到峰值。预测倾向于低估季中log10计数。预测误差和零的比例之间呈强烈的负相关性showed.ConclusionField人口是不可预测的和随机的，无论类烟碱种子治疗。这一结果给决策支持提出了一个问题，无法有效地提供一个单一的区域性解决方案。加权置换熵推断M. persicae 12.2 m吸捕器时间序列具有中等至低的内在可预测性。使用移徙模式的预警往往预测的数量低于观察到的数量。© 2022 The Authors.Pest Management Sciencepublished by John Wiley & Sons Ltd代表化学工业协会。
BackgroundSugar beet is threatened by virus yellows, a disease complex vectored by aphids that reduces sugar content. We present an analysis ofMyzus persicaepopulation dynamics with and without neonicotinoid seed treatment. We use 6 years' yellow water trap and field‐collected aphid data and two decades of 12.2 m suction‐trap aphid migration data. We investigate both spatial synchrony and forecasting error to understand the structure and spatial scale of field counts and why forecasting aphid migrants lacks accuracy. Our aim is to derive statistical parameters to inform regionwide pest management strategies.ResultsSpatial synchrony, indicating the coincident change in counts across the region over time, is rarely present and is best described as stochastic. Uniquely, early season field populations in 2019 did show spatial synchrony to 90 km compared to the overall average weekly correlation length of 23 km. However, 70% of the time series were spatially heterogenous, indicating patchy between‐field dynamics. Field counts lacked the same seasonal trend and did not peak in the same week. Forecasts tended to under‐predict mid‐season log10counts. A strongly negative correlation between forecasting error and the proportion of zeros was shown.ConclusionField populations are unpredictable and stochastic, regardless of neonicotinoid seed treatment. This outcome presents a problem for decision‐support that cannot usefully provide a single regionwide solution. Weighted permutation entropy inferred thatM. persicae12.2 m suction‐trap time series had moderate to low intrinsic predictability. Early warning using a migration model tended to predict counts at lower levels than observed. © 2022 The Authors.Pest Management Sciencepublished by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.