Calibration and application of quality-scoring functions using soil-forest productivity relationships in land reclamation

Abstract

Soil-forest productivity has been studied over decades, especially for North American boreal forests; however, there has been little effort to quantitatively incorporate this relationship into frameworks of soil quality assessment (SQA). The need for such framework is critical as land reclamation and ecosystem restoration are expected to quantitatively demonstrate the redevelopment of functional soil-plant systems in spatial and/or temporal dimensions for closure of disturbed sites. The objective of this research was to assess three potential options for calibrating soil-forest productivity relationships into a SQA framework using scoring functions, while demonstrating applications in land reclamation. Using Alberta oil sands reclamation as a case study, soil-forest productivity was calibrated by i) stepwise regression of soil and forest productivity indicators, ii) use of GYPSY to model pre-disturbance growth trajectories while treating soil as categorical variable, and iii) use of process based models HYDRUS 1D and BIOMES-BGC to estimate soil and plant productivity parameters such as available water holding capacity, leaf area index and net primary productivity. All three approaches provided adequate data for calibrating the relationship into existing SQA frameworks producing soil quality-scoring functions (SQF), although the regression approach will require more rigorous validation and constraining of the SQF in comparison to the other two options. Applications of the SQF include temporal assessments of plant’s growth rate of reclaimed stands and testing the effect of reclamation cover design factors on forest productivity.