Universidad Complutense de Madrid
E-Prints Complutense

Leaf dry matter content is better at predicting aboveground net primary production than specific leaf area



Último año

Smart, Simon Mark y Glanville, Helen Catherine y Blanes, María del Carmen y Mercado, Lina María y Emmett, Bridget Anne y Jones, David Leonard y Cosby, Bernard Jackson y Marrs, Robert Hunter y Butler, Adam y Marshall, Miles Ramsvik y Reinsch, Sabine y Herrero-Jáuregui, Cristina y Hodgson, John Gavin (2017) Leaf dry matter content is better at predicting aboveground net primary production than specific leaf area. Functional Ecology, 31 (6). pp. 1336-1344. ISSN 0269-8463, ESSN: 1365-2435

[img] PDF
Restringido a Sólo personal autorizado del repositorio


URL Oficial: http://onlinelibrary.wiley.com/doi/10.1111/1365-2435.12832/full


1. Reliable modelling of above-ground net primary production (aNPP) at fine resolution is a significant challenge. A promising avenue for improving process models is to include response and effect trait relationships. However, uncertainties remain over which leaf traits are correlated most strongly with aNPP.
2. We compared abundance-weighted values of two of the most widely used traits from the leaf economics spectrum (specific leaf area and leaf dry matter content) with measured aNPP across a temperate ecosystem gradient.
3. We found that leaf dry matter content (LDMC) as opposed to specific leaf area (SLA) was the superior predictor of aNPP (R2 = 0 55).
4. Directly measured in situ trait values for the dominant species improved estimation of aNPP significantly. Introducing intraspecific trait variation by including the effect of replicated trait values from published databases did not improve the estimation of aNPP.
5. Our results support the prospect of greater scientific understanding for less cost because LDMC is much easier to measure than SLA.

Tipo de documento:Artículo
Palabras clave:Bayesian modelling; Ecosystem function; Global change; Intraspecific variation; Measurement error
Materias:Ciencias Biomédicas > Biología > Ecología
Código ID:43819
Depositado:07 Jul 2017 10:22
Última Modificación:07 Jul 2017 10:22

Descargas en el último año

Sólo personal del repositorio: página de control del artículo