Plant Growth Regulation

, Volume 84, Issue 2, pp 333–339 | Cite as

Kin recognition in plants with distinct lifestyles: implications of biomass and nutrient niches

Original paper
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Abstract

Kin recognition has been demonstrated by plant biomass allocation and morphology traits as well as by nitrogen (N) uptake, but has not been examined from a nutrient-niche view yet. In this study, four species with distinct lifestyles, including Glycine max (L.) Merr. (herbaceous legume), Belamcanda chinensis (L.) DC. (herbaceous non-legume), Caesalpinia pulcherrima (L.) Sw. (woody legume), and Populus tomentosa (L.) Carr. (woody non-legume) were used to demonstrate kin recognition by estimating their biomass and allocation, as well as nutrient niches based on their uptake efficiency for N, phosphorus (P), sulfur (S), potassium (K), calcium (Ca), magnesium (Mg), and iron (Fe). For G. max, kin recognition was achieved by increased biomass, and by reduced nutrient-uptake efficiency of N, P, S, K, Ca, Mg, and Fe (decreased nutrient niches) to decrease nutrient competition among kin plants compared to the strangers. Although B. chinensis and C. pulcherrima had no biomass response, kin plants of B. chinensis increased, whereas C. pulcherrima decreased their S-uptake efficiency compare to strangers. Therefore, kin competition occurred in B. chinensis through increased nutrient niche whereas kin recognition occurred in C. pulcherrima through decreased nutrient niche. By comparison, P. tomentosa showed the co-occurrence of kin recognition and competition by increased root allocation and decreased P-uptake efficiency. These findings suggest that the biomass allocation and plant nutrient niches based on their nutrient-uptake efficiency can be used as potential parameters to identify kin recognition.

Keywords

Biomass Nutrient niches Nutrient uptake efficiency Kin recognition Lifestyles 

Notes

Acknowledgements

We thanked Luyang Dong from China Internet Network Information Center for help looking after the plant seedlings. This study is supported by National Natural Science Foundation of China (31470560).

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© Springer Science+Business Media B.V., part of Springer Nature 2017

Authors and Affiliations

  1. 1.Key Laboratory of Land Surface Pattern and Simulation, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural ResourcesChinese Academy of SciencesBeijingChina
  2. 2.State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijingChina

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