Literature DB >> 33863150

Functional leaf attributes predict litter decomposition rate in herbaceous plants.

J H C Cornelissen1, K Thompson1.   

Abstract

We tested the hypothesis that functional attributes of living leaves provide a basis for predicting the decomposition rate of leaf litter. The data were obtained from standardized screening tests on 38 British herbaceous species. Graminoid monocots had physically tougher leaves with higher silicon contents than did herbaceous dicots, and this corresponded with the lesser decomposibility of the former. Total base content of living leaves was a good predictor of litter decomposition rate, but the evolutionary and ecological basis for this relationship appeared to differ between graminoid monocots and herbaceous dicots. In the monocots, litter decomposition rate was strongly predicted by leaf potassium content, which appeared to reflect other growth- related plant attributes such as seedling maximum relative growth rate, foliar nitrogen and phosphorus content, specific leaf area and short leaf lifespan. In the dicots the relationship between total leaf base content and litter decomposition rate was not unambiguously explained by growth-related leaf attributes, possibly because of the considerable calcium uptake by dicots, which varies according to calcium availability in the soil.

Entities:  

Keywords:  Cations; growth rate; leaf attributes; litter decomposition; nutrients

Year:  1997        PMID: 33863150     DOI: 10.1046/j.1469-8137.1997.00628.x

Source DB:  PubMed          Journal:  New Phytol        ISSN: 0028-646X            Impact factor:   10.151


  2 in total

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Authors:  Katrin Heisse; Christiane Roscher; Jens Schumacher; Ernst-Detlef Schulze
Journal:  Oecologia       Date:  2007-03-14       Impact factor: 3.298

2.  Long-term effects of artificial nighttime lighting and trophic complexity on plant biomass and foliar carbon and nitrogen in a grassland community.

Authors:  Vinka Anic; Kevin J Gaston; Thomas W Davies; Jonathan Bennie
Journal:  Ecol Evol       Date:  2022-08-04       Impact factor: 3.167

  2 in total

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