Correlations among leaf traits provide a significant constraint on the estimate of global gross primary production

By Ying-Ping Wang, Xingjie Lu, Ian J. Wright, Yongjiu Dai, Peter J. Rayner, P. B. Reich. 2012

114 citations recorded by the source corpus.

Subfields: Ecology, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/90bee8da7669844d57d7fc2bf65c99cc36c92e6e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

1. Peter B. Reich
2. D. Binkley
3. Åke Berg
4. Rune Halvorsen
5. H. Wagner
6. G. De’ath
7. A. Ramette

In Global and Planetary Change

1. Peter B. Reich
2. B. Medlyn
3. I. C. Prentice
4. Ying Ping Wang
5. I. Wright
6. M. Westoby
7. D. Forrester
8. U. Niinemets

Citations in the corpus

• The world‐wide ‘fast–slow’ plant economics spectrum: a traits manifesto (2014, methodology): “A third trait-based approach was taken by Wang et al. (2012) who incorporated multi-leaf trait covariance ([N], LMA, leaf life span) into CABLE.”
• Reliable, robust and realistic: the three R's of next-generation land-surface modelling (2014, methodology): “Using the CABLE LSM (Kowalczyk et al., 2006; Wang et al., 2010, 2011), Wang et al. (2012) calculated the global mean and standard deviation of modelled GPP using two groups of 500 randomly sampled sets of the three leaf traits n, τ and m with15 their observed means and standard deviations.”