BACKGROUND AND AIMS: Fodder provision in species-rich grasslands, i.e. herbage growth, proportion of leaf, and leaf and stem digestibility, is difficult to predict for short periods of time, such as between two defoliations or less. The value of two methods based on plant traits for evaluating these agronomic properties was examined. METHODS: One method is based on plant trait measurements on the plant community (leaf dry matter content, plant height, flowering date); the other is on vegetation composition expressed as plant functional types (acquisitive versus conservative PFTs) established by measuring leaf dry matter content on pure grass stands. The experiment consisted of 18 fields with three different defoliation regimes (combinations of cutting and grazing) and two levels of fertilization. To establish a growth curve over the first growth cycle, herbage was sampled about 10 times in spring. KEY RESULTS: Coefficients of correlation between agronomic properties of the vegetation and its functional composition were higher when the latter was assessed through PFT and an indicator of the plant nutrient status (Ni) instead of measured plant traits. The date at which the ceiling yield occurred for the standing herbage mass or only the leaf component, which varied by up to 500 degree-days between treatments, and the leaf proportion, depended entirely on the PFT, and largely so for the leaf digestibility. The standing herbage mass at the time of ceiling yield depended only on Ni, or mainly so in the case of the daily herbage growth rate. Similar plant digestibility between plant communities was found at flowering time, although there were big differences in PFT composition. The shape of the growth curve was flatter when there was great functional diversity in the plant community. CONCLUSIONS: The PFT composition and the Ni were more reliable than the plant functional traits measured in the field for evaluating herbage growth pattern and digestibility in spring.
BACKGROUND AND AIMS: Fodder provision in species-rich grasslands, i.e. herbage growth, proportion of leaf, and leaf and stem digestibility, is difficult to predict for short periods of time, such as between two defoliations or less. The value of two methods based on plant traits for evaluating these agronomic properties was examined. METHODS: One method is based on plant trait measurements on the plant community (leaf dry matter content, plant height, flowering date); the other is on vegetation composition expressed as plant functional types (acquisitive versus conservative PFTs) established by measuring leaf dry matter content on pure grass stands. The experiment consisted of 18 fields with three different defoliation regimes (combinations of cutting and grazing) and two levels of fertilization. To establish a growth curve over the first growth cycle, herbage was sampled about 10 times in spring. KEY RESULTS: Coefficients of correlation between agronomic properties of the vegetation and its functional composition were higher when the latter was assessed through PFT and an indicator of the plant nutrient status (Ni) instead of measured plant traits. The date at which the ceiling yield occurred for the standing herbage mass or only the leaf component, which varied by up to 500 degree-days between treatments, and the leaf proportion, depended entirely on the PFT, and largely so for the leaf digestibility. The standing herbage mass at the time of ceiling yield depended only on Ni, or mainly so in the case of the daily herbage growth rate. Similar plant digestibility between plant communities was found at flowering time, although there were big differences in PFT composition. The shape of the growth curve was flatter when there was great functional diversity in the plant community. CONCLUSIONS: The PFT composition and the Ni were more reliable than the plant functional traits measured in the field for evaluating herbage growth pattern and digestibility in spring.
Authors: A Hector; B Schmid; C Beierkuhnlein; M C Caldeira; M Diemer; P G Dimitrakopoulos; J A Finn; H Freitas; P S Giller; J Good; R Harris; P Hogberg; K Huss-Danell; J Joshi; A Jumpponen; C Korner; P W Leadley; M Loreau; A Minns; C P Mulder; G O'Donovan; S J Otway; J S Pereira; A Prinz; D J Read; M Scherer-Lorenzen; E D Schulze; A S D Siamantziouras; E M Spehn; A C Terry; A Y Troumbis; F I Woodward; S Yachi; J H Lawton Journal: Science Date: 1999-11-05 Impact factor: 47.728
Authors: Eric Garnier; Sandra Lavorel; Pauline Ansquer; Helena Castro; Pablo Cruz; Jiri Dolezal; Ove Eriksson; Claire Fortunel; Helena Freitas; Carly Golodets; Karl Grigulis; Claire Jouany; Elena Kazakou; Jaime Kigel; Michael Kleyer; Veiko Lehsten; Jan Leps; Tonia Meier; Robin Pakeman; Maria Papadimitriou; Vasilios P Papanastasis; Helen Quested; Fabien Quétier; Matt Robson; Catherine Roumet; Graciela Rusch; Christina Skarpe; Marcelo Sternberg; Jean-Pierre Theau; Aurélie Thébault; Denis Vile; Maria P Zarovali Journal: Ann Bot Date: 2006-11-03 Impact factor: 4.357
Authors: Sandra Díaz; Sandra Lavorel; Francesco de Bello; Fabien Quétier; Karl Grigulis; T Matthew Robson Journal: Proc Natl Acad Sci U S A Date: 2007-12-19 Impact factor: 11.205
Authors: Iris Bumb; Eric Garnier; Sylvain Coq; Johanne Nahmani; Maria Del Rey Granado; Olivier Gimenez; Elena Kazakou Journal: Ann Bot Date: 2018-03-05 Impact factor: 4.357