嵌套
种间竞争
生态网络
生态学
群落结构
稳健性(进化)
网络结构
生物
灵活性(工程)
生态系统
生物多样性
计算机科学
数学
统计
分布式计算
基因
生物化学
作者
Paul J. CaraDonna,Nickolas M. Waser
出处
期刊:Oikos
[Wiley]
日期:2020-05-25
卷期号:129 (9): 1369-1380
被引量:63
摘要
Ecological communities consist of species that are joined in complex networks of interspecific interaction. These interactions often form and dissolve rapidly, but this temporal variation is not well integrated into our understanding of the causes and consequences of network structure. If interspecific interactions exhibit temporal flexibility across time periods over which organisms co-occur, then the emergent structure of the corresponding network may also be flexible, something that a temporally-static perspective will miss. Here, we use an empirical plant–pollinator system to examine short-term (week-to-week) flexibility in network structure (connectance, nestedness and specialization) and in the individual species interactions that contribute to that structure across three summer growing seasons in a subalpine ecosystem. We then compared the properties of weekly networks to the properties of cumulative networks that aggregate field observations over each full summer season. As a test of the potential robustness of networks to perturbation, we also simulated the random loss of species from weekly networks. A week-to-week view reveals considerable flexibility in the interactions of individual species and their contributions to network structure. For example, species that would be considered relatively generalized across their entire activity period may be much more specialized at certain times, and at no point as generalized as the cumulative network may suggest. Furthermore, a week-to-week view reveals corresponding flexibility in network structure and potential robustness throughout each summer growing season. We conclude that short-term flexibility in species interactions leads to short-term variation in network properties, and that a cumulative, season-long perspective may miss important aspects of the way in which species interact, with implications for understanding their ecology, evolution and conservation.
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