Suppr超能文献

集合群落模型预测自然系统中局部-区域物种丰富度关系。

Metacommunity models predict the local-regional species richness relationship in a natural system.

作者信息

Hugueny Bernard, Cornell Howard V, Harrison Susan

机构信息

IRD, Laboratoire d'ecologie des hydrosystèmes fluviaux, Université Lyon 1, 43 Boulevard du 11 Novembre 1918, 69622 Villeurbanne, France.

出版信息

Ecology. 2007 Jul;88(7):1696-706. doi: 10.1890/06-1884.1.

Abstract

Many natural communities exhibit positive relationships between local and regional species richness (LSR-RSR relationships), which can be either linear or curvilinear. Previous models have shown that the form of this relationship depends on the relative rates of colonization and extinction and the sensitivity of these rates to competition. We use simple models to show that the LSR-RSR relationship also depends on the type of metacommunity structure (Levins-like or mainland-island), and our models generate a wider range of realistic forms than do most previous models. We parameterize and test our models with two independent data sets for Daphnia in rock pools on islands in Finland and Sweden. We find that the Levins-like model with competition correctly predicts the observed LSR-RSR relationship and provides the best fit to the average local species richness per island. Simulations show that our models are robust to relaxing our assumption of identical species properties. Our study is one of the first to make and successfully test quantitative predictions for how a widely studied community pattern, the LSR-RSR relationship, arises from metacommunity dynamics.

摘要

许多自然群落呈现出局部物种丰富度与区域物种丰富度之间的正相关关系(LSR - RSR关系),这种关系可以是线性的,也可以是曲线的。先前的模型表明,这种关系的形式取决于定殖和灭绝的相对速率以及这些速率对竞争的敏感性。我们使用简单模型表明,LSR - RSR关系还取决于集合群落结构的类型(类莱文斯模型或大陆 - 岛屿模型),并且我们的模型生成的现实形式范围比大多数先前模型更广。我们使用芬兰和瑞典岛屿上岩池中水蚤的两个独立数据集对我们的模型进行参数化和测试。我们发现具有竞争的类莱文斯模型正确地预测了观察到的LSR - RSR关系,并最能拟合每个岛屿的平均局部物种丰富度。模拟表明,我们的模型对于放宽物种特性相同的假设具有鲁棒性。我们的研究是首批针对广泛研究的群落模式——LSR - RSR关系如何从集合群落动态中产生进行定量预测并成功测试的研究之一。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验