Soil quality assessment for peat-mineral mix cover soil used in oil sands reclamation.

Abstract

A soil quality (SQ) assessment and rating framework that is quantitative, iterative, and adaptable, with justifiable weighting for quality scores, is required for evaluating site-specific SQ at land reclamation sites. Such a framework needs to identify the minimum dataset that reflects the current knowledge regarding relationships between SQ indicators and relevant measures of ecosystem performance. Our objective was to develop nonlinear scoring functions for assessing the impact on SQ of peat-mineral mix (PMM) used as a cover soil at land reclamation sites. Soil functional indicators affected by PMM were extracted from existing databases and correlated with soil organic carbon (SOC). Based on defined objectives for SQ assessment, indicators with significant correlation ( < 0.05) to SOC were selected, normalized, and fitted to sigmoid functions using nonlinear regression procedure to establish SQ functions (SQFs) that can analyze changes in field capacity, permanent wilting point, soil nitrogen, and cation exchange capacity of PMM using SOC as input parameter. Application of the SQFs to an independent dataset produced ratings with mean differences similar to the treatment effects of mixing three levels of peat and mineral soil. These results show that derived ratings and weighing factors using SOC reflect the relationship between PMM treatment and other SQ indicators. Applying the developed SQFs to a long-term soil monitoring dataset shows that an increase or decrease in SOC from 10 to 20 g kg causes a significant change in SQ. This identifies the need for further nutrient and moisture management of PMM to support long-term SQ development in land reclamation.