Determination of exchangeable hydrogen ions in boreal shield soils of Quebec

Abstract

An unbuffered BaCl2 extraction for determining effective cation exchange capacity (ECEC) and exchangeable cations is often used for acidic forest soils. However, the contribution of exchangeable H+ to ECEC cannot be assessed using this method as H+ in the extract may be produced/consumed in reactions with free Al3+ and Al-OH complexes, or H+ may be added to the extract via non-exchangeable sources. Fundamentally, any valid measure of ECEC must include some estimate of exchangeable H+ concentration or a demonstration that it is negligible. Unfortunately, this procedure is often neglected in forest soil studies. In this paper, we assessed the significance of the contribution of exchangeable H+ to ECEC for upper soil horizons of three sites of Quebec’s Boreal Shield subject to various disturbance types (i.e., recent harvest, fire and mature forest). We also investigated whether the linear relationships between exchangeable H+ concentrations and soil pH are robust enough to develop regression models capable of predicting exchangeable H+. Exchangeable H+ in the FH samples was higher than that in the podzolic B samples, but the amount of adsorbed H+ relative to ECEC was nevertheless significant in the podzolic B horizons. The general linear relationship (i.e., FH and podzolic B samples as a single data set) developed from soil pH in water explained close to 70% of the variability of log (H+/ECEC). The relationships between log (exchangeable H+) and pH in water in the FH samples were however superior (R2 ≥ 80), either for all sites, disturbance types and sampling strategies (e.g., proportions of F and H horizons in sample). The relationships developed for podzolic B samples alone were not as strong, but ECEC was used efficiently in combination with soil pH to increase prediction capabili ties (R2 ≥ 0.61). Key words: Boreal Shield forest soils, effective cation exchange capacity, exchangeable H+, fire, FH and podzolic B horizons, harvesting, prediction models, soil pH.