The study acknowledges reliance on models and site-scale evidence for understanding forest management's impact on climate change, indicating a lack of real-world, large-scale empirical data to support their conclusions.
Coarse Spatial Resolution
The spatial resolutions of the datasets used (25x25 km² for SMOS and 500x500 m² for MODIS) are too coarse to accurately capture the fine-scale dynamics of forest management practices, such as harvesting and regeneration, leading to potential over- or underestimation of carbon stocks and fluxes.
Incomplete Carbon Accounting
The study focuses on aboveground biomass, neglecting changes in other carbon pools like soil carbon, litter, and coarse woody debris, which could significantly influence the overall carbon balance of the region.
The assumption that forest probability is directly related to the fraction of a grid covered by forest is not rigorously validated, potentially leading to inaccuracies in assessing forest cover change.
Classification Challenges
Frequent small-scale changes between tree planting and harvesting make accurate classification challenging, especially when using moderate-resolution satellite data.
Discrepancy with Previous Studies
The study's estimates of carbon stock increases are significantly higher than previous studies, raising concerns about the accuracy and reliability of the methodology used.
Incomplete Lifecycle Analysis
The study doesn't account for the full lifecycle of extracted wood, including its processing and ultimate fate (e.g., decomposition, combustion), which affects the long-term carbon sequestration potential.