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pycoalescence and rcoalescence: Packages for simulating spatially explicit neutral models of biodiversity
Methods in Ecology and Evolution ( IF 6.6 ) Pub Date : 2020-07-15 , DOI: 10.1111/2041-210x.13451
Samuel E. D. Thompson 1, 2 , Ryan A. Chisholm 1 , James Rosindell 2
Affiliation  

  1. Neutral theory proposes that some macroscopic biodiversity patterns can be explained in terms of drift, speciation and immigration, without invoking niches. There are many different varieties of neutral model, all assuming that the fitness of an individual is unrelated to its species identity. Variants that are spatially explicit provide a means for making quantitative predictions about spatial biodiversity patterns.
  2. We present software packages that make spatially explicit neutral simulations straightforward and efficient. The packages allow the user to customize both dispersal and landscape structure in a wide variety of ways. We provide a Python package pycoalescence and a functionally equivalent R package rcoalescence. In both packages, the core routines are written in C++ and make use of coalescence methods to optimize performance.
  3. We explain the technical details of the packages and give examples for their application, with a particular focus on two scenarios of ecological and evolutionary interest—a landscape with habitat fragmentation, and an archipelago of islands.
  4. Spatially explicit neutral models represent an important tool in ecology for understanding the processes of biodiversity generation and predicting outcomes at large scales. The effort required to implement these complex spatially explicit simulations efficiently has thus far been a barrier to entry. Our packages increase the accessibility of these models and encourage further investigation of the primary mechanisms underpinning biodiversity.


中文翻译:

pyalalescence和rcoalescence:用于模拟生物多样性在空间上明确的中性模型的软件包

  1. 中立理论提出,可以用漂移,物种形成和移民的方式来解释一些宏观的生物多样性模式,而无需利基。中性模型有许多不同的种类,所有这些都假设一个人的适应能力与其物种身份无关。在空间上明确的变体提供了一种对空间生物多样性模式进行定量预测的方法。
  2. 我们提供的软件包可直接有效地进行空间明确的中性模拟。这些软件包允许用户以多种方式自定义分散结构和景观结构。我们提供了Python包pycoalescence和功能上等效的R包rcoalescence。在这两个软件包中,核心例程都是用C ++编写的,并利用合并方法来优化性能。
  3. 我们解释了这些软件包的技术细节,并举例说明了这些软件包的应用,尤其着重于两种生态和进化利益情景:一个栖息地破碎的景观和一个群岛群岛。
  4. 明确的空间中性模型是生态学中了解生物多样性产生过程和大规模预测结果的重要工具。迄今为止,有效地实施这些复杂的空间显式模拟所需的工作一直是入门的障碍。我们的软件包增加了这些模型的可访问性,并鼓励进一步研究支持生物多样性的主要机制。
更新日期:2020-07-15
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