A network model for plant-pollinator community assembly

被引:80
|
作者
Campbell, Colin [1 ]
Yang, Suann [2 ]
Albert, Reka [1 ,2 ]
Shea, Katriona [2 ]
机构
[1] Penn State Univ, Dept Phys, University Pk, PA 16802 USA
[2] Penn State Univ, Dept Biol, University Pk, PA 16802 USA
基金
美国国家科学基金会;
关键词
mutualism; transition graph; bipartite; ANIMAL MUTUALISTIC NETWORKS; FOOD-WEB STRUCTURE; ECOLOGICAL COMMUNITIES; SPECIES-DIVERSITY; COMPLEX NETWORKS; BUMBLE BEES; BIODIVERSITY; COMPETITION; EVOLUTION; PATTERNS;
D O I
10.1073/pnas.1008204108
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Community assembly models, usually constructed for food webs, are an important component of our understanding of how ecological communities are formed. However, models for mutualistic community assembly are still needed, especially because these communities are experiencing significant anthropogenic disturbances that affect their biodiversity. Here, we present a unique network model that simulates the colonization and extinction process of mutualistic community assembly. We generate regional source pools of species interaction networks on the basis of statistical properties reported in the literature. We develop a dynamic synchronous Boolean framework to simulate, with few free parameters, the dynamics of new mutualistic community formation from the regional source pool. This approach allows us to deterministically map out every possible trajectory of community formation. This level of detail is rarely observed in other analytic approaches and allows for thorough analysis of the dynamical properties of community formation. As for food web assembly, we find that the number of stable communities is quite low, and the composition of the source pool influences the abundance and nature of community outcomes. However, in contrast to food web assembly, stable mutualistic communities form rapidly. Small communities with minor fluctuations in species presence/absence (self-similar limit cycles) are the most common community outcome. The unique application of this Boolean network approach to the study of mutualistic community assembly offers a great opportunity to improve our understanding of these critical communities.
引用
收藏
页码:197 / 202
页数:6
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