Diagnosis of forest soil sensitivity to harvesting residues removal – A transfer study of soil science knowledge to forestry practitioners. (September 2019) - Durante, Samuel; Augusto, Laurent; Achat, David L.; Legout, Arnaud; Brédoire, Félix; Ranger, Jacques; Seynave, Ingrid; Jabiol, Bernard; Pousse, Noémie
Graphical abstract: Highlights: We chose a proxy of the preponderance of nutrients biological cycling for French forest ecosystems. We derived a soil sensitivity indicator to harvesting residues removal based on soil chemical analysis. We simplified this indicator in order to create a simple, rapid, low-cost and reasonably reliable diagnosis tool. Abstract: Forest biomass is a source of renewable energy that can contribute to meeting international targets for reducing greenhouse gas emissions. However, removing forest harvesting residues may cause important nutrient losses. Because negative effects of increased nutrient removal are not systematic, forest managers need tools for soil sensitivity assessment, to decide whether they can or not increase biomass harvesting without impairing long term forest productivity and health. This study follows two goals: (i) define forest ecosystem sensitivity indicators derived from soil physico-chemical analyses and (ii) build and test a simplified tool that predicts such soil sensitivity. After screening international literature, nutrient concentration in the topsoil was chosen as the simplest and currently most accurate indicator of soil sensitivity. With a consolidated database on French forest soils, we built diagnostic keys that predict soil sensitivity using only five parameters: humus form, topsoil texture, depth of CaCO3 apparition, ecological region, and rooting depth. We performed a statistical evaluation of the simplified tool on independent data sets and evaluated it in the field with potential users. As compared with the existing French forest soils sensitivity indicator, our diagnosis tool displayed lower high and low sensitivities classification errors and allowed to differentiate sensitivity into five elemental ones (Ca, Mg, K, P and N). All participating end users agreed with the necessity of such indicator and appreciated the simplicity of diagnosis with our tool. This study shows a complete research and development process, from the translation of scientific knowledge into an indicator of sustainable forest management to the simplification for assimilation.