Functional Traits 2.0: The power of the metabolome for ecology

代谢组 生物 生态学 动物生态学 功能生态学 特质 生态系统生态学 进化生态学 现象 生态系统 植物生态学 代谢组学 社区 生物信息学 计算机科学 表型 生物化学 基因 寄主(生物学) 程序设计语言
作者
Tom W. N. Walker,Jake M. Alexander,Pierre‐Marie Allard,Oliver Baines,Virginie Baldy,Richard D. Bardgett,Pol Capdevila,Phyllis D. Coley,Bruno David,Emmanuel Défossez,María‐José Endara,Madeleine Ernst,Catherine Fernandez,Dale L. Forrister,Albert Gargallo‐Garriga,Vincent E. J. Jassey,Sue Marr,Steffen Neumann,Loïc Pellissier,Josep Peñuelas
出处
期刊:Journal of Ecology [Wiley]
卷期号:110 (1): 4-20 被引量:89
标识
DOI:10.1111/1365-2745.13826
摘要

Abstract A major aim of ecology is to upscale attributes of individuals to understand processes at population, community and ecosystem scales. Such attributes are typically described using functional traits, that is, standardised characteristics that impact fitness via effects on survival, growth and/or reproduction. However, commonly used functional traits (e.g. wood density, SLA) are becoming increasingly criticised for not being truly mechanistic and for being questionable predictors of ecological processes. This Special Feature reviews and studies how the metabolome (i.e. the thousands of unique metabolites that underpin physiology) can enhance trait‐based ecology and our understanding of plant and ecosystem functioning. In this Editorial, we explore how the metabolome relates to plant functional traits, with reference to life‐history trade‐offs governing fitness between generations and plasticity shaping fitness within generations. We also identify solutions to challenges of acquiring, interpreting and contextualising metabolome data, and propose a roadmap for integrating the metabolome into ecology. We next summarise the seven studies composing the Special Feature, which use the metabolome to examine mechanisms behind plant community assembly, plant‐organismal interactions and effects of plants and soil micro‐organisms on ecosystem processes. Synthesis . We demonstrate the potential of the metabolome to improve mechanistic and predictive power in ecology by providing a high‐resolution coupling between physiology and fitness. However, applying metabolomics to ecological questions is currently limited by a lack of conceptual, technical and data frameworks, which needs to be overcome to realise the full potential of the metabolome for ecology.
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