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空间种群模型中的资源明确型相互作用。

Resource-explicit interactions in spatial population models.

作者信息

Champer Samuel E, Chae Bryan, Haller Benjamin C, Champer Jackson, Messer Philipp W

机构信息

Department of Computational Biology, Cornell University, Ithaca, NY 14853.

Center for Bioinformatics, School of Life Sciences, Center for Life Sciences, Peking University, Beijing, China 100871.

出版信息

bioRxiv. 2024 Jan 15:2024.01.13.575512. doi: 10.1101/2024.01.13.575512.

Abstract

Continuous-space population models can yield significantly different results from their panmictic counterparts when assessing evolutionary, ecological, or population-genetic processes. However, the computational burden of spatial models is typically much greater than that of panmictic models due to the overhead of determining which individuals interact with one another and how strongly they interact. Though these calculations are necessary to model local competition that regulates the population density, they can lead to prohibitively long runtimes. Here, we present a novel modeling method in which the resources available to a population are abstractly represented as an additional layer of the simulation. Instead of interacting directly with one another, individuals interact indirectly via this resource layer. We find that this method closely matches other spatial models, yet can dramatically increase the speed of the model, allowing the simulation of much larger populations. Additionally, models structured in this manner exhibit other desirable characteristics, including more realistic spatial dynamics near the edge of the simulated area, and an efficient route for modeling more complex heterogeneous landscapes.

摘要

在评估进化、生态或种群遗传过程时,连续空间种群模型可能会产生与其随机交配模型截然不同的结果。然而,由于确定哪些个体相互作用以及相互作用强度的额外计算量,空间模型的计算负担通常比随机交配模型大得多。尽管这些计算对于模拟调节种群密度的局部竞争是必要的,但它们可能导致运行时间长得令人望而却步。在这里,我们提出了一种新颖的建模方法,其中种群可用的资源被抽象地表示为模拟的附加层。个体不是直接相互作用,而是通过这个资源层间接相互作用。我们发现这种方法与其他空间模型非常匹配,但可以显著提高模型的速度,从而能够模拟更大的种群。此外,以这种方式构建的模型还具有其他理想的特性,包括在模拟区域边缘附近更逼真的空间动态,以及为模拟更复杂的异质景观提供了一条有效途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bce/10827080/f759da9a63aa/nihpp-2024.01.13.575512v1-f0001.jpg

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