Development of a hazard map for oak wilt disease in Japan
Development of a hazard map for oak wilt disease in Japan
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DOI：
10.1111/afe.12098
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发表时间：
2015-05-01
影响因子：
1.6
通讯作者：
Makino, Shun'ichi
中科院分区：
文献类型：
--
作者：
Kondoh, Hiroshi;Yamanaka, Takehiko;Makino, Shun'ichi
基于Logistic回归模型，我们构建了日本山形和福岛县的橡树枯萎病危害图。在回归模型的框架内，我们纳入了来自以前受损地区的植被类型、地理和气象以及虫害迁徙的数据。我们使用下一年同一地区的落叶记录来评估模型的预测能力。山形县的结果具有很高的预测性，我们得出结论，可以根据前一年的破坏记录结合其他环境数据构建实用的危险地图。通过纳入移民效应，该模型的预测价值得到了显著提高。用来预测山形县损失的模型仅对福岛县实际损失的46.7%是正确的。关于该模式在其他县的应用，确定了若干困难。基于我们的结果，我们建议在构建包含移民的本地化回归模型时，应在目标区快速收集落叶数据。收集和组织落叶数据可以帮助在给定年份开始发生橡树枯萎病之前快速绘制危险地图。
We constructed a hazard map for oak wilt disease in Yamagata and Fukushima Prefectures, Japan, based on a logistic regression model. Within the framework of a regression model, we incorporated data from previously damaged areas on vegetation type, geography and meteorology, and pest immigration. We evaluated the predictive power of the model using defoliation records within the same prefecture taken from the subsequent year. The results obtained for Yamagata Prefecture were highly predictive and we conclude that practical hazard maps can be constructed based on damage records from the previous year combined with other environmental data. The predictive value of the model was improved dramatically by incorporating an immigration effect. The model used to predict damage in Yamagata Prefecture was correct for only 46.7% of the actual damage in Fukushima Prefecture. Several difficulties were identified regarding the application of the model in other prefectures. Based on our results, we suggest that defoliation data should be collected quickly in the target area when constructing a localized regression model that includes immigration. Collection and organization of defoliation data could help to quickly draw up hazard maps before oak wilt disease begins to occur in a given year.