An integrated method for high-resolution definition of new diameter-based fine root sub-classes of Fagus sylvatica L.

Abstract

Key message: Compared to the traditional approach, applying micrometric image analysis to fine root samples of Fagus sylvatica with subsequent data treatment through principal component and cluster analysis yielded specific diameter sizes for fine root sub-classes having better resolution of the corresponding branching orders, and a more coherent relationship with the values of annual production and turnover rate. Context: Fine root traits are poorly understood, impeding an accurate representation of terrestrial biogeochemical models. Traditionally used, arbitrary diameter thresholds lead to a misestimation of fine root traits such as branching order, environmental relationship, annual production, and turnover rate. Aims: Here, we present, as modification of the traditional method, an integrated approach to segregate, at high-resolution, fine root populations of Fagus sylvatica into new diameter sub-classes that better correspond with the traits mentioned above. Methods: Samples, collected with a sequential soil coring method, were subjected to a micrometric image analysis, and resultant data were treated with principal component and cluster analysis. Results: Results showed that fine roots were distributed into diameter-size sub-classes (0–0.3 mm, 0.3–1 mm, and 1–2 mm) different from those determined by traditional methods (0–0.5 mm, 0.5–1 mm, and 1–2 mm). New sub-classes provided a better resolution of the corresponding branching-orders, and the values of annual production and turnover rate were more coherent with diameter class and soil depth. Moreover, new sub-classes provided a more precise match with soil temperature than traditional methods. Conclusion: Our method may help to unveil fine root dynamics and development, reduce data analysis time, and make the diameter-based classification more precise and trustworthy even in the case of non-intact samples.