超越聚合范式:互惠网络中的物候和结构

IF 2.6 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Journal of Physics Complexity Pub Date : 2024-05-13 DOI:10.1088/2632-072x/ad459e
Clàudia Payrató-Borràs, Carlos Gracia-Lázaro, Laura Hernández and Yamir Moreno
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引用次数: 0

摘要

互惠互利关系是自然生态系统的重要组成部分。利用生态网络来表示物种及其生态互动关系,可以研究不同生态系统共有的结构和动态模式。然而,如果忽略了互惠群落的时间维度,就会失去对自然生态系统的组织和功能的相关认识。因此,结合经验物候学--物种在一个季节内的活动周期--来充分理解时间变化对网络结构的影响至关重要。在本文中,我们利用经验数据集和一组合成模型,提出了一个框架来描述植物授粉者群落的物候特征,并评估物候如何重塑其网络形象。对三个实证案例的分析表明,将相互作用网络表述为静态时会遗漏一些重要信息,从而导致高估基本结构特征的价值。我们讨论了我们的发现对互惠关系和同类竞争共同资源的影响。我们的研究表明,记录的相互作用和物种的活动持续时间是准确复制观察到的互助群落模式的关键因素。此外,我们对合成模型的探索强调了物候学驱动机制的系统特异性,加深了我们对自然生态系统复杂性的理解。
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Beyond the aggregated paradigm: phenology and structure in mutualistic networks
Mutualistic relationships, where species interact to obtain mutual benefits, constitute an essential component of natural ecosystems. The use of ecological networks to represent the species and their ecological interactions allows the study of structural and dynamic patterns common to different ecosystems. However, by neglecting the temporal dimension of mutualistic communities, relevant insights into the organization and functioning of natural ecosystems can be lost. Therefore, it is crucial to incorporate empirical phenology -the cycles of species’ activity within a season- to fully understand the impact of temporal variability on network architecture. In this paper, by using empirical datasets together with a set of synthetic models, we propose a framework to characterize the phenology of plant-pollinator communities and assess how it reshapes their portrayal as a network. Analyses of three empirical cases reveal that non-trivial information is missed when representing the network of interactions as static, which leads to overestimating the value of fundamental structural features. We discuss the implications of our findings for mutualistic relationships and intra-guild competition for common resources. We show that recorded interactions and species’ activity duration are pivotal factors in accurately replicating observed patterns within mutualistic communities. Furthermore, our exploration of synthetic models underscores the system-specific character of the mechanisms driving phenology, increasing our understanding of the complexities of natural ecosystems.
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来源期刊
Journal of Physics Complexity
Journal of Physics Complexity Computer Science-Information Systems
CiteScore
4.30
自引率
11.10%
发文量
45
审稿时长
14 weeks
期刊最新文献
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