Multi-objective optimization of an ecological assembly model
Multi-objective optimization of an ecological assembly model
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DOI：
10.1016/j.ecoinf.2007.02.001
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发表时间：
2007-01-01
影响因子：
5.1
通讯作者：
Sabourin, Robert
中科院分区：
文献类型：
--
作者：
Cote, Pascal;Parrott, Lael;Sabourin, Robert
本工作的目的是使用多目标进化算法（MOEA）参数化的生态组装模型的基础上Lotka-Volterra动力学。在群落组装模型中，物种是根据入侵序列从一个物种库中引入的。通过操纵组装序列，我们看看最终社区的结构，获得了一个多目标的过程，其目标是优化最终社区的生产力。MOEA还必须满足这样的约束，即以这种方式构建的社区具有特定的连通性。针对多目标优化问题，采用非支配排序算法（NSGA-II）和强度Pareto进化算法（SPEA 2）对序列进行优化。结果表明，使用优化序列的组装过程中产生不同的社区结构比那些通过随机序列产生的。首先，组合的社区比从随机序列中获得的社区更有生产力。我们表明，这种生产力的提高是由于社区食物网的度分布，这是重塑的优化过程。此外，使用相同的区域物种池的MOEA能够产生不同的预期连接的社区。这些结果表明，NSGA-II和SPEA 2优化生态模型中的参数的有效性。(c)2007 Elsevier B. V.保留所有灯光。
The aim of the present work is to use multi-objective evolutionary algorithms (MOEA) to parameterise an ecological assembly model based on Lotka-Volterra dynamics. In community assembly models, species are introduced from a pool of species according to a sequence of invasion. By manipulating the assembly sequences, we look at the structure of the final communities obtained by a multi-objective process where the goal is to optimize the productivity of the final communities. The MOEA must also meet the constraint that the communities constructed in this fashion have a specified connectance. The Non-dominated Sorting Algorithm (NSGA-II) and the Strength Pareto Evolutionary Algorithm (SPEA2) were employed to optimize sequences according to the multi-objective optimization problem. The results show that the assembly process using optimized sequences generated different community structure than those generated via random sequences. First, the assembled communities are much more productive than those obtained from random sequences. We show that this increase of productivity is due to the degree distribution of the community food web, which was reshaped by the optimization process. In addition, using identical regional species pools the MOEAs were able to generate communities of different expected connectances. These results demonstrate the effectiveness of NSGA-II and SPEA2 for optimizing parameters in ecological models. (c) 2007 Elsevier B.V. All lights reserved.