Table 2 Guidance table for assessing model adequacy and data quality
From: Setting the forest reference levels in the European Union: overview and challenges
Main components and description (based on the theoretical approach from [52]) | Covered aspects | Examples of adequacy levels |
|---|---|---|
Model adequacy: Capacity of the model to simulate the development of forest carbon pools and relevant type of forest management practices and natural disturbances | Age—Simulation of age-related forest characteristics | Ability of the model to incorporate age-related proxies: Highly adequate—explicit run of age or other maturity-related parameters (individual tree size, volume classes, biomass density classes) Adequate—implicit run of age-class based on aggregated data reported in the historical GHG inventory, which assumes that age-structure would not change Partly adequate—a constant value is used |
Management—Simulation of forest management practices, and natural disturbances | Consideration of harvest intensity: Highly adequate—narrow specifications of thinning and final cuts as explicit characteristics of forest management practices and natural disturbances Adequate—broad specifications of thinning and final cuts as explicit characteristics of forest management practices, and proxies for natural disturbances Partly adequate—implicit consideration of management activities on thinning and final cuts. Natural disturbances not considered | |
Pools—Incorporation of forest carbon pools | Forest carbon pools as included in the modelling approach: from mandatory pools in the LULUCF Regulation (i.e. living biomass and deadwood) [model highly adequate] to only one pool [model partly adequate] Highly adequate—modelling of C stocks and transfers among pools at disaggregated level in spatial and temporal terms Adequate—modelling of C stocks and transfers among pools at an aggregated level in spatial terms Partly adequate—multiple and non-integrated modelling framework used for simulations of each C pools (e.g. simplified models) | |
Data quality: Consistency of the input data | Type and quality of the input data | Use of relevant data and information sources and period matching the period 2000–2009, and consistency of data with model’s requirement (are any other assumptions made, how strong effect those assumptions are expected to have) Complete—data retrieved corresponds to modelling needs and reflects status and dynamic of anthropogenic intervention and natural disturbances in the forests Partly complete—part of the data needs to be gap filled and reconstructed based on available data Incomplete—data is missing so only expert assumptions are used as a proxy to obtain the required information on forest status and dynamic |