【2h】

Generic assembly patterns in complex ecological communities

机译:复杂生态社区中的通用装配模式

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摘要

The study of ecological communities often involves detailed simulations of complex networks. However, our empirical knowledge of these networks is typically incomplete and the space of simulation models and parameters is vast, leaving room for uncertainty in theoretical predictions. Here we show that a large fraction of this space of possibilities exhibits generic behaviors that are robust to modeling choices. We consider a wide array of model features, including interaction types and community structures, known to generate different dynamics for a few species. We combine these features in large simulated communities, and show that equilibrium diversity, functioning, and stability can be predicted analytically using a random model parameterized by a few statistical properties of the community. We give an ecological interpretation of this “disordered” limit where structure fails to emerge from complexity. We also demonstrate that some well-studied interaction patterns remain relevant in large ecosystems, but their impact can be encapsulated in a minimal number of additional parameters. Our approach provides a powerful framework for predicting the outcomes of ecosystem assembly and quantifying the added value of more detailed models and measurements.
机译:生态社区的研究通常涉及复杂网络的详细模拟。但是,我们对这些网络的经验知识通常是不完整的,并且仿真模型和参数的空间很大,为理论预测中的不确定性留下了空间。在这里,我们表明,这种可能性空间的很大一部分表现出对建模选择具有鲁棒性的一般行为。我们考虑了各种各样的模型特征,包括相互作用类型和群落结构,这些特征已知会为几种物种产生不同的动力学。我们在大型模拟社区中结合了这些功能,并表明可以使用由社区的一些统计属性参数化的随机模型来分析预测平衡多样性,功能和稳定性。我们对这种“无序”限制进行了生态学的解释,即结构无法从复杂性中脱颖而出。我们还证明,在大型生态系统中,一些经过深入研究的交互模式仍然有意义,但是可以将它们的影响封装在最少数量的其他参数中。我们的方法提供了一个强大的框架,可用于预测生态系统组装的结果并量化更详细的模型和度量的附加值。

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