Predicting leaf traits of herbaceous species from their spectral characteristics

Ecology and Evolution

Hans D. Roelofsen²  Peter M. van Bodegom³  Lammert Kooistra¹ 

[1] Laboratory for Geo-Information Science and Remote Sensing, Wageningen University, Wageningen, The Netherlands;KWR Watercycle Research Institute, Nieuwegein, The Netherlands;Department of Ecological science, Subdepartment Systems Ecology, VU University, Amsterdam, The Netherlands

关键词: Herbaceous species;    leaf spectroscopy;    leaf traits;    small width leaves;   

DOI  :  10.1002/ece3.932

来源: Wiley

【 摘 要 】

Abstract

Trait predictions from leaf spectral properties are mainly applied to tree species, while herbaceous systems received little attention in this topic. Whether similar trait–spectrum relations can be derived for herbaceous plants that differ strongly in growing strategy and environmental constraints is therefore unknown. We used partial least squares regression to relate key traits to leaf spectra (reflectance, transmittance, and absorbance) for 35 herbaceous species, sampled from a wide range of environmental conditions. Specific Leaf Area and nutrient-related traits (N and P content) were poorly predicted from any spectrum, although N prediction improved when expressed on a per area basis (mg/m² leaf surface) instead of mass basis (mg/g dry matter). Leaf dry matter content was moderately to good correlated with spectra. We explain our results by the range of environmental constraints encountered by herbaceous species; both N and P limitations as well as a range of light and water availabilities occurred. This weakened the relation between the measured response traits and the leaf constituents that are truly responsible for leaf spectral behavior. Indeed, N predictions improve considering solely upper or under canopy species. Therefore, trait predictions in herbaceous systems should focus on traits relating to dry matter content and the true, underlying drivers of spectral properties.

【 授权许可】

CC BY   
© 2014 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.