Kuparinen Anna
Department of Mathematics and Statistics, PO Box 68, 00014 The University of Helsinki, Helsinki, Finland.
Trends Plant Sci. 2006 Jun;11(6):296-301. doi: 10.1016/j.tplants.2006.04.006. Epub 2006 May 11.
The growing need for ecological forecasts of, for example, species migration, has increased interest in developing mechanistic models for wind dispersal of seeds, pollen and spores. Analytical models are only able to predict mean dispersal distances, whereas sophisticated trajectory simulation models are able to incorporate rare wind conditions causing long-distance dispersal and are therefore preferable. Despite the rapid development of mechanistic dispersal models, only a few studies have focused on comparing the performance of the models. To assess the level of model complexity needed, attention should be paid to model comparisons and the sensitivity of the predictions to model complexity. In addition to studying the movement of airborne particles, future modelling work should also focus on the processes of particle release and deposition.
例如，对物种迁移等生态预测的需求不断增长，这使得人们对开发用于种子、花粉和孢子风力传播的机理模型的兴趣增加。分析模型只能预测平均传播距离，而复杂的轨迹模拟模型能够纳入导致长距离传播的罕见风况，因此更具优势。尽管机理传播模型发展迅速，但只有少数研究关注模型性能的比较。为了评估所需的模型复杂度水平，应关注模型比较以及预测对模型复杂度的敏感性。除了研究空气中颗粒的运动，未来的建模工作还应关注颗粒释放和沉积的过程。
