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Keywords:

  • litter decomposition;
  • litter quality;
  • near-infrared spectrometry;
  • tropical forest

Abstract

Plant-litter chemical quality is an important driver of many ecosystem processes, however, what actually constitutes high- or low-quality litter (chemical potential for fast and slow decomposition, respectively) is often interpreted by the indices available. Here, near-infrared spectroscopy (NIRS) was used to explore leaf-litter chemical quality and the controls on decomposition in the tropical rainforest region of north Queensland Australia. Leaf-litter samples from litterfall collections and litterbag studies were used. NIRS was used to calibrate the chemical compositions of the material (N, P, C, Mg, Ca, acid detergent fiber, acid detergent lignin, α-cellulose, and total phenolics) from a smaller sample set covering the spectral range in the full set of samples. Calibrations were compared for both separate (local) and combined models, for litterbags, and litterfall. Coefficients of determination (r2) in the local models ranged from 0.88 (litterbag Mg) to 0.99 (litterfall N), with residual prediction deviation ratios > 3 for all constituents except Mg (≈ 2.5). Mass loss in the litterbags was strongly related to the NIR spectra, with model r2's of 0.75 (in situ leaves) and 0.76 (common control leaf). In situ decomposability was determined from modeling the initial NIR spectra prior to decomposition with litterbag exponential-decay rates (model r2 of 0.81, n = 85 initial samples). A best subset model including litter-quality, climate, and soil variables predicted decay better than the NIR decomposability model (r2 = 0.87). For litter quality alone the NIR model predicted decay rate better than all of the best predictive litter–chemical quality indices. The decomposability model was used to predict in situ decomposability in the litterfall samples. The chemical variables explaining NIR decomposability for litterfall were initial P, C, and phenolics (linear model r2 = 0.80, n = 2471). NIRS is a holistic technique that is just as, if not more accurate, than litter–chemical quality indices, when predicting decomposition and decomposability, shown here in a regional field study.