Reflectance spectroscopy allows rapid, accurate and non‐destructive estimates of functional traits from pressed leaves

Abstract

Abstract More than ever, ecologists seek to employ herbarium collections to estimate plant functional traits from the past and across biomes. However, many trait measurements are destructive, which may preclude their use on valuable specimens. Researchers increasingly use reflectance spectroscopy to estimate traits from fresh or ground leaves, and to delimit or identify taxa. Here, we extend this body of work to non‐destructive measurements on pressed, intact leaves, like those in herbarium collections. Using 618 samples from 68 species, we used partial least‐squares regression to build models linking pressed‐leaf reflectance spectra to a broad suite of traits, including leaf mass per area (LMA), leaf dry matter content (LDMC), equivalent water thickness, carbon fractions, pigments, and twelve elements. We compared these models to those trained on fresh‐ or ground‐leaf spectra of the same samples. The traits our pressed‐leaf models could estimate best were LMA (R2 = 0.932; %RMSE = 6.56), C (R2 = 0.855; %RMSE = 9.03), and cellulose (R2 = 0.803; %RMSE = 12.2), followed by water‐related traits, certain nutrients (Ca, Mg, N, and P), other carbon fractions, and pigments (all R2 = 0.514–0.790; %RMSE = 12.8–19.6). Remaining elements were predicted poorly (R2 20). For most chemical traits, pressed‐leaf models performed better than fresh‐leaf models, but worse than ground‐leaf models. Pressed‐leaf models were worse than fresh‐leaf models for estimating LMA and LDMC, but better than ground‐leaf models for LMA. Finally, in a subset of samples, we used partial least‐squares discriminant analysis to classify specimens among 10 species with near‐perfect accuracy (>97%) from pressed‐ and ground‐leaf spectra, and slightly lower accuracy (>93%) from fresh‐leaf spectra. These results show that applying spectroscopy to pressed leaves is a promising way to estimate leaf functional traits and identify species without destructive analysis. Pressed‐leaf spectra might combine advantages of fresh and ground leaves: like fresh leaves, they retain some of the spectral expression of leaf structure; but like ground leaves, they circumvent the masking effect of water absorption. Our study has far‐reaching implications for capturing the wide range of functional and taxonomic information in the world’s preserved plant collections.

Keywords

• functional traits
• herbarium collections
• leaf chemistry
• partial least‐squares regression (PLSR)
• reflectance spectroscopy
• species identification