种内竞争
特质
局部适应
适应(眼睛)
变化(天文学)
竞赛(生物学)
生物
选择(遗传算法)
进化生物学
生态学
人口
群落结构
计算机科学
社会学
人口学
人工智能
神经科学
程序设计语言
物理
天体物理学
作者
Jonas Wickman,Thomas Koffel,Christopher A. Klausmeier
摘要
AbstractHow is trait diversity in a community apportioned between and within coevolving species? Disruptive selection may result in either a few species with large intraspecific trait variation (ITV) or many species with different mean traits but little ITV. Similar questions arise in spatially structured communities: heterogeneous environments could result in either a few species that exhibit local adaptation or many species with different mean traits but little local adaptation. To date, theory has been well-equipped to either include ITV or to dynamically determine the number of coexisting species, but not both. Here, we devise a theoretical framework that combines these facets and apply it to the above questions of how trait variation is apportioned within and between species in unstructured and structured populations, using two simple models of Lotka-Volterra competition. For unstructured communities, we find that as the breadth of the resource spectrum increases, ITV goes from being unimportant to crucial for characterizing the community. For spatially structured communities on two patches, we find no local adaptation, symmetric local adaptation, or asymmetric local adaptation, depending on how much the patches differ. Our framework provides a general approach to incorporate ITV in models of eco-evolutionary community assembly.
科研通智能强力驱动
Strongly Powered by AbleSci AI