Dahlem Centre of Plant Science (DCPS), Freie Universität Berlin, Institute for Biology, Altensteinstr. 6, 14195, Berlin, Germany.
Berlin-Brandenburg Institute of Advanced Biodiversity Research (BBIB), Altensteinstr. 6, 14195, Berlin, Germany.
New Phytol. 2017 Dec;216(4):1130-1139. doi: 10.1111/nph.14748. Epub 2017 Sep 12.
Root traits are often thought to be analogues of leaf traits along the plant economics spectrum. But evolutionary pressures have most likely shaped above- and belowground patterns differentially. Here, we aimed to identify the most important aboveground traits for explaining root traits without an a priori focus on known concepts. We measured morphological root traits in a glasshouse experiment on 141 common Central European grassland species. Using random forest algorithms, we built predictive models of six root traits from 97 aboveground morphological, ecological and life history traits. Root tissue density was best predicted by leaf dry matter content, whereas traits related to root fineness were best predicted by diaspore mass: the heavier the diaspore, the coarser the root system. Specific leaf area (SLA) was not an important predictor for any of the root traits. This study confirms the hypothesis that root traits are more than analogues of leaf traits within a plant economics spectrum. The results reveal a novel ecological pattern and highlight the power of root data to close important knowledge gaps in trait-based ecology.
根特性通常被认为是沿植物经济谱的叶特性的类似物。但进化压力很可能使地上和地下模式产生了不同的影响。在这里,我们旨在确定最重要的地上特性,以便在没有先验关注已知概念的情况下解释根特性。我们在温室实验中测量了 141 种常见的中欧草原物种的形态根特性。使用随机森林算法,我们从 97 种地上形态、生态和生活史特性中构建了 6 种根特性的预测模型。根组织密度最好由叶片干物质含量预测,而与根细度相关的特性最好由胞子质量预测:胞子越重,根系越粗。比叶面积(SLA)不是任何根特性的重要预测因子。本研究证实了根特性不仅仅是植物经济谱内叶特性的类似物这一假设。研究结果揭示了一种新的生态模式,并强调了根数据在基于特征的生态学中弥补重要知识差距的力量。