Glob Chang Biol. 2026 Apr;32(4):e70868. doi: 10.1111/gcb.70868.
ABSTRACT
Detecting changes in forest soil carbon stocks is critical for compiling national carbon budgets, yet remains challenging due to high spatial variability and relatively small temporal changes. Here, we use data from Canada’s National Forest Inventory (NFI), which includes repeated measurements of organic and mineral soil horizons across 532 plots. We quantified within- and between-plot variability in soil carbon properties, assessed minimum detectable differences (MDD), and explored design improvements through simulations. Spatial variation in soil carbon stocks was substantial: coefficients of variation were ~40% for mineral and ~70% for organic horizons, with within-plot comparable to between-plot variability. Consequently, MDDs were also high, at ~4.1 and 4.6 Mg ha-1 10 year-1 for the surface mineral and organic horizons, respectively. This implies that only large, widespread changes would be detectable with the current data. Simulations showed that increasing the number of remeasurement plots to ~700 with four subsamples per plot could reduce MDD to be on par with the current estimate of soil carbon change. Grouping plots by ecozone provided inconsistent benefits at the national level because of ecozones with high spatial heterogeneity. The data also had patterns consistent with the statistical phenomenon of regression to the mean, which implies that any change in carbon stock may be a statistical artifact. Indeed, soil carbon stocks appeared to grow by 2.3 Mg C ha-1 10 year-1 during the first remeasurement interval, while a small number of second remeasurement interval data showed a completely unrelated pattern supporting the inference that this first interval change was a statistical artifact. Overall, our analysis of the NFI data suggests that its design characteristics of sampling multiple microplots per main plot and collecting longitudinal data per microplot are critical to providing robust estimates of soil carbon stock changes that can be used in national greenhouse gas inventories.
PMID:42037479 | DOI:10.1111/gcb.70868
