文章基本信息

标题：Asymmetric ecological conditions favor Red-Queen type of continued evolution over stasis
本地全文：下载
作者：Jan Martin Nordbotten ; Nils C. Stenseth
期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2016
卷号：113
期号：7
页码：1847-1852
DOI：10.1073/pnas.1525395113
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：Four decades ago, Leigh Van Valen presented the Red Queen’s hypothesis to account for evolution of species within a multispecies ecological community [Van Valen L (1973) Evol Theory 1(1):1–30]. The overall conclusion of Van Valen’s analysis was that evolution would continue even in the absence of abiotic perturbations. Stenseth and Maynard Smith presented in 1984 [Stenseth NC, Maynard Smith J (1984) Evolution 38(4):870–880] a model for the Red Queen’s hypothesis showing that both Red-Queen type of continuous evolution and stasis could result from a model with biotically driven evolution. However, although that contribution demonstrated that both evolutionary outcomes were possible, it did not identify which ecological conditions would lead to each of these evolutionary outcomes. Here, we provide, using a simple, yet general population-biologically founded eco-evolutionary model, such analytically derived conditions: Stasis will predominantly emerge whenever the ecological system contains only symmetric ecological interactions, whereas both Red-Queen and stasis type of evolution may result if the ecological interactions are asymmetrical, and more likely so with increasing degree of asymmetry in the ecological system (i.e., the more trophic interactions, host–pathogen interactions, and the like there are [i.e., +/− type of ecological interactions as well as asymmetric competitive (−/−) and mutualistic (+/+) ecological interactions]). In the special case of no between-generational genetic variance, our results also predict dynamics within these types of purely ecological systems.
关键词：coevolution ; evolution within ecological communities ; ecosystem structure ; mathematical modeling ; mathematical analysis