Root traits are more than analogues of leaf traits: the case for diaspore mass

被引:74
作者
Bergmann, Joana [1 ,2 ]
Ryo, Masahiro [1 ,2 ]
Prati, Daniel [3 ]
Hempel, Stefan [1 ,2 ]
Rillig, Matthias C. [1 ,2 ]
机构
[1] Free Univ Berlin, DCPS, Inst Biol, Altensteinstr 6, D-14195 Berlin, Germany
[2] Berlin Brandenburg Inst Adv Biodivers Res BBIB, Altensteinstr 6, D-14195 Berlin, Germany
[3] Univ Bern, Inst Plant Sci, Altenbergrain 21, CH-3013 Bern, Switzerland
关键词
Central European grassland species; dispersal distance; plant economics spectrum; random forest model; seed mass; soil fungi (mycorrhiza); specific leaf area (SLA); specific root length (SRL); LIFE-HISTORY TRAITS; PLANT ECONOMICS SPECTRUM; SEED DISPERSAL; INTRASPECIFIC VARIABILITY; EUROPEAN FLORA; DIVERSITY; DATABASE; ASSOCIATION; MYCORRHIZAS; PHYLOGENIES;
D O I
10.1111/nph.14748
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
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.
引用
收藏
页码:1130 / 1139
页数:10
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