Comparing methods for building trophic spectra of ecological data

The distribution of biomass, production, and catches over trophic levels (TLs) of the foodweb has been shown theoretically and empirically to provide powerful insights into ecosystem functioning and the effects of fishing. One approach for building trophic spectra of ecological data is based on smoothing original data and assuming zeroes when no values are available for a TL (smoothing- based method). An alternative method is proposed, based on the distribution of ecological data according to density functions (dispersion-based method), and a systematic review of the different alternatives is presented. Six different methods for building trophic spectra, i. e. the smoothing-based and five alternative forms for dispersion-based (using normal, lognormal, and Weibull distributions, also including shifted lognormal and Weibull with zero at TL 2), were applied to ecological properties (i. e. production, biomass, and catches) derived for 24 foodweb models to test their relative performance. The smoothing-based method suffers from the lack of consistency with original data and from unrealistic emergent properties, such as transfer efficiency. The analysis demonstrates the advantages of the dispersion-based method for overcoming these issues and shows, using transfer efficiencies estimated from the models (flow-based estimates) as a reference, that the normal density distribution function performs better.