Improved scaling of minirhizotron data using an empirically-derived depth of field and correcting for the underestimation of root diameters

Accurate data on the standing crop, production, and turnover of fine roots is essential to our understanding of major terrestrial ecological processes. Minirhizotrons offer a unique opportunity to study the dynamic processes of root systems, but are susceptible to several measurement biases. We use roots extracted from minirhizotron tube surfaces to calculate the depth of field of a minirhizotron image and present a model to correct for the underestimation of root diameters obscured by soil in minirhizotron images. Non-linear regression analysis resulted in an estimated depth of field of 0.78 mm for minirhizotron images. Unadjusted minirhizotron data underestimated root net primary production and fine root standing crop by 61 % when compared to adjusted data using our depth of field and root diameter corrections. Changes in depth of field accounted for > 99 % of standing crop adjustments with root diameter corrections accounting for < 1 %. Our results represent the first effort to empirically derive depth of field for minirhizotron images. This work may explain the commonly reported underestimation of fine roots using minirhizotrons, and stands to improve the ability of researchers to accurately scale minirhizotron data to large soil volumes.