Forecasting Cameraria ohridella invasion dynamics in recently invaded countries:: from validation to prediction
Forecasting Cameraria ohridella invasion dynamics in recently invaded countries:: from validation to prediction
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DOI：
10.1111/j.1365-2664.2005.01074.x
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发表时间：
2005-10-01
影响因子：
5.7
通讯作者：
Augustin, S
中科院分区：
文献类型：
--
作者：
Gilbert, M;Guichard, S;Augustin, S
1. 生物入侵具有人为根源，尽管许多物种能够在新入侵的地区自行传播，但显示出加速传播速度的长距离传播事件通常与人类活动有关。之前的研究对德国七叶斑潜蝇Camararia ohridella扩散的几种入侵模型的性能进行了比较，结果表明，考虑到人口密度对长距离扩散事件概率的影响，定性和定量方面最好的模型是分层扩散模型。 2．法国在 4 年间（2000 年至 2004 年，5274 个观察点）收集了类似的数据。这些数据用于使用原始参数评估德国最佳拟合模型的性能，并模拟潜叶蝇在法国的传播情况。3。德国开发的考虑人口密度变化的分层扩散模型预测了法国的入侵，其预测能力与该模型所在地区的预测能力相似。这表明，在具有相似环境条件的新入侵国家中，可以预期具有同等水平的可预测性。4。根据 2002 年至 2004 年对英国 Cameraria 的首次观测，我们应用该模型预测了 2005 年至 2008 年英国未来的入侵动态。根据不同的主要环境条件讨论了预测。5．合成与应用。本研究中开发的模型和预测提供了新入侵国家入侵先验模型的少数例子之一，并提供了一个简单的建模框架，可用于探索其他入侵生物体的传播。就Cameraria而言，我们几乎无法阻止或减缓其传播，但我们的模型通过预测分布和传播速度的变化，提供了有害害虫种群可能出现的地点和时间的预警。
1. Biological invasions have an anthropogenic origin, and although many species are able to spread on their own within the newly invaded area, long-distance dispersal events shown to accelerate rates of spread are frequently associated with human activities. In a previous study, the performances of several invasion models of the spread of the horse chestnut leafminer Cameraria ohridella in Germany were compared, demonstrating that the best model in qualitative and quantitative terms was a stratified dispersal model taking into account the effect of human population density on the probability of long-distance dispersal events.2. Similar data were collected in France over 4 years (2000-2004, 5274 observation points). These data were used to assess the performance of the best-fit models from Germany using the original parameters and to model the spread of the leafminer in France.3. The stratified dispersal model accounting for variations in human population density developed in Germany, predicted the invasion of France with a similar level of predictive power as in the area where it was developed. This suggests that an equivalent level of predictability can be expected in a newly invaded country with similar environmental conditions.4. We applied the model to forecast the future invasion dynamics in the UK from 2005 to 2008, based on the first observations of Cameraria in the country in 2002-2004. Predictions are discussed in the light of different prevailing environmental conditions.5. Synthesis and application. The model and predictions developed in this study provide one of the few examples of an a priori model of invasion in a newly invaded country, and provide a simple modelling framework that can be used to explore the spread of other invading organisms. In the case of Cameraria, little can be done to prevent or slow its spread but our model, by predicting changes in distribution and rates of spread, provides fore-warning of where and when damaging pest populations are likely to appear.