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Allometric Trophic Networks From Individuals to Socio-Ecosystems: Consumer–Resource Theory of the Ecological Elephant in the Room

机译:来自个人的各种营养网络到社会生态系统:房间里生态大象的消费资源理论

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A well-known parable is that of the blind men studying an elephant each of which assert the elephant is the part they first hold in their hands e.g., “rope!” says the tail holder while the leg holder asserts “tree!” The various subdisciplines of ecology appear similar in that we each engage in our enthusiastic but at least somewhat myopic study with a remarkably limited agreement or even discussion about the overall system which we all study. Allometric trophic network (ATN) theory offers a path out of this dilemma by integrating across scales, taxa, habitats and organizational levels from physiology to ecosystems based on consumer-resource interactions among co-existing organisms. The network architecture and the metabolic and behavioral processes that determine the structure and dynamics of these interactions form the first principles of ATN theory, which in turn provides a synthetic overview and powerfully predictive framework for ecology from organisms to ecosystems. Beyond ecology, ATN theory also synthesizes eco-evolutionary and socio-ecological research still largely based on consumer-resource mechanisms but respectively integrated with processes including natural selection and market mechanisms. This paper briefly describes foundations, advances, and future directions of ATN theory including predicting an ecosystem’s phenotype from its community’s genotype in order to accelerate more predictive and unified understanding of the complex systems studied by ecologists and other environmental scientists.
机译:一个众所周知的寓言是盲人学习大象的盲人,这些人都断言大象是他们首次握在他们手中的一部分,例如,“绳子!”杠杆持有人说“树!”生态学的各种次校长显得相似,因为我们每人都搞我的热情,但至少有些近视学习,这是一个非常有限的协议甚至讨论我们所有研究的整体系统。各种营养网络(ATN)理论通过基于共存生物中的消费者资源相互作用,通过将尺度,分类群,栖息地和组织水平与生态系统相结合,提供了一种困境的路径。确定这些相互作用的结构和动态的网络架构和代谢和行为过程形成了ATN理论的第一个原则,这反过来为生态系统的生态学提供了合成概述和有力预测的框架。除了生态学之外,ATN理论还综合了生态进化和社会生态研究仍然基于消费者资源机制,但分别与包括自然选择和市场机制的过程一体化。本文简要介绍了ATN理论的基础,进展和未来方向,包括预测来自其社区的基因型的生态系统的表型,以加速对生态学家和其他环境科学家研究的复杂系统的更具预测和统一理解。

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