Departamento de Fisica Aplicada, Universidad de Granada, Avda. Fuentenueva s/n, 18071 Granada, Spain.
Math Biosci Eng. 2014 Jun;11(3):573-97. doi: 10.3934/mbe.2014.11.573.
Functional response estimation and population tracking in predator-prey systems are critical problems in ecology. In this paper we consider a stochastic predator-prey system with a Lotka-Volterra functional response and propose a particle filtering method for: (a) estimating the behavioral parameter representing the rate of effective search per predator in the functional response and (b) forecasting the population biomass using field data. In particular, the proposed technique combines a sequential Monte Carlo sampling scheme for tracking the time-varying biomass with the analytical integration of the unknown behavioral parameter. In order to assess the performance of the method, we show results for both synthetic and observed data collected in an acarine predator-prey system, namely the pest mite Tetranychus urticae and the predatory mite Phytoseiulus persimilis.
功能反应估计和捕食者-猎物系统中的种群跟踪是生态学中的关键问题。在本文中，我们考虑了一个具有Lotka-Volterra 功能反应的随机捕食者-猎物系统，并提出了一种粒子滤波方法，用于：（a）估计代表功能反应中每个捕食者有效搜索率的行为参数；（b）使用现场数据预测种群生物量。特别是，所提出的技术将用于跟踪时变生物量的序列蒙特卡罗采样方案与未知行为参数的分析积分相结合。为了评估该方法的性能，我们展示了在一种螨类捕食者-猎物系统中收集的合成和观测数据的结果，即害螨桃蚜和捕食螨智利小植绥螨。
