An optimized fine root sampling methodology balancing accuracy and time investment

Abstract

Aims Tree roots are spatially highly heterogeneous and it thus requires large numbers of samples to detect statistically significant changes in root biomass. The objectives of this study were to understand and quantify the sources of error in the assessment of fine root biomass (<2 mm) during the second year of a highdensity Populus plantation. Methods Soil cores were collected in winter (n035) and in summer (n020), and fine roots were picked by hand for varying lengths of time: 1, 2, 5, 20, 40, and 60 min. The root biomass data were used to identify the best combination of the time spent for root picking and the number of samples collected, that minimizes the overall uncertainty (i.e. the combination of the spatial error due to the incomplete sampling and the temporal error due to the incomplete core processing). Results On average, 25 min was enough time to pick 90 % of the fine root biomass in winter, while in summer only 10 min were needed. In winter fewer samples were needed, but more time for picking was necessary as compared to summer when root biomass was higher. Conclusions Fine root sampling can be optimized by minimizing the uncertainty of the biomass estimates and simultaneously decreasing root sampling time investment.