Abstract
Abstract. Understanding the causes of variation in functional plant traits is a central issue in ecology, particularly in the context of global change. Spectroscopy is increasingly used for rapid and non-destructive estimation of foliar traits, but few studies have evaluated its accuracy when assessing phenotypic variation in multiple traits. Working with 24 chemical and physical leaf traits of six European tree species growing on strongly contrasting soil types (i.e. deep alluvium versus nearby shallow chalk), we asked (i) whether variability in leaf traits is greater between tree species or soil type, and (ii) whether field spectroscopy is effective at predicting intraspecific variation in leaf traits as well as interspecific differences. Analysis of variance showed that interspecific differences in traits were generally much stronger than intraspecific differences related to soil type, accounting for 25 % versus 5 % of total trait variation, respectively. Structural traits, phenolic defences and pigments were barely affected by soil type. In contrast, foliar concentrations of rock-derived nutrients did vary: P and K concentrations were lower on chalk than alluvial soils, while Ca, Mg, B, Mn and Zn concentrations were all higher, consistent with the findings of previous ecological studies. Foliar traits were predicted from 400 to 2500 nm reflectance spectra collected by field spectroscopy using partial least square regression, a method that is commonly employed in chemometrics. Pigments were best modelled using reflectance data from the visible region (400–700 nm), while all other traits were best modelled using reflectance data from the shortwave infrared region (1100–2500 nm). Spectroscopy delivered accurate predictions of species-level variation in traits. However, it was ineffective at detecting intraspecific variation in rock-derived nutrients (with the notable exception of P). The explanation for this failure is that rock-derived elements do not have absorption features in the 400–2500 nm region, and their estimation is indirect, relying on elemental concentrations covarying with structural traits that do have absorption features in that spectral region (constellation effects). Since the structural traits did not vary with soil type, it was impossible for our regression models to predict intraspecific variation in rock-derived nutrients via constellation effects. This study demonstrates the value of spectroscopy for rapid, non-destructive estimation of foliar traits across species, but highlights problems with predicting intraspecific variation indirectly. We discuss the implications of these findings for mapping functional traits by airborne imaging spectroscopy.
Highlights
There is currently great interest in using plant traits to understand the influence of environmental filtering and species identity on the functioning of plant communities and to model community responses to the environmental change (MacGillivray et al, 1995; McGill et al, 2006; Green et al, 2008; Funk et al, 2016)
Hemicellulose, cellulose, lignin and leaf mass per unit areas (LMA) were completely unaffected by soil type, and pigments and traits related to water status (δ13C and water content) varied little with soil type, with the exception of carotenoids concentration, which was 25 % higher in alluvial soil
K does not have absorption features in the 400–2500 nm range, but K concentration is highly correlated to leaf water content, soluble carbon, lignin, hemicellulose and cellulose, all of which have absorbance features in the region. The importance of these constellation effects becomes apparent when we examine the partitioning of variance of PLSR-predicted trait values: several rock-derived nutrients vary significantly with soil type when measured in leaves (Fig. 1) but little of that variation is successfully modelled by www.biogeosciences.net/14/3371/2017/
Summary
There is currently great interest in using plant traits to understand the influence of environmental filtering and species identity on the functioning of plant communities and to model community responses to the environmental change (MacGillivray et al, 1995; McGill et al, 2006; Green et al, 2008; Funk et al, 2016). Traits vary at multiple scales within individuals, within populations, between populations and between species (Albert et al, 2011), and analysis of this variation is key to evaluating the strength of various filtering processes on communities growing along environmental gradients (Davey et al, 2009; Violle et al, 2012). Global analyses of leaf nitrogen, phosphorus and leaf mass per unit areas (LMA) indicate that about half of all variation occurs within communities (Wright et al, 2004), underscoring the importance of community-level variation in traits
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