Towards the application of soil organic matter as an indicator of forest ecosystem productivity: Deriving thresholds, developing monitoring systems, and evaluating practices

Soil organic matter (SOM), typically measured as soil organic carbon (SOC), has been widely recognized as a critical linkage between forest management and long-term site productivity. However, its use as an indicator of sustainable forest management practices has been limited both by difficulties in detecting changes in soil carbon due to inherent high variability and by challenges associated with determining appropriate thresholds for loss. In this study we evaluate a methodology for using field measures of total SOC (forest floor to 60 cm depth in mineral soil) in conjunction with a mechanistic forest growth model to derive threshold values for total SOC with respect to the maintenance of ecosystem productivity for a lodgepole pine (Pinus contorta) forest in the central interior region of British Columbia. We also examine the practicality of implementing a sustainable forest management (SFM) monitoring program around this measure and the potential long-term impact of alternative management scenarios on the indicator. SOC contents for the different site types sampled in the Quesnel region ranged from 35 to 57 t ha−1. Long-term simulations of biomass extraction over several rotations showed a near 1:1 ratio in the relative decline of ecosystem productivity associated with relative declines in total SOC. A power analysis revealed that a mean sampling intensity of n = 12–25 and n = 8–17 would be required to detect 20% and 30% losses of total SOC, respectively, depending on the level of statistical power desired. The sampling intensity required for an effective monitoring program was significantly reduced by summing SOC for all soil layers to limit sampling error related to determination of layer boundaries. A modelling analysis of the effect of rotation length on SOC for the Quesnel forest types, suggests that rotation lengths shorter than 75 years should be avoided to prevent declines in ecosystem productivity. Our results confirm that the combination of modelling and statistical techniques can be successfully used to develop cost-efficient monitoring plans of sustainability of forest management, with SOC as a valid indicator of ecosystem productivity.