ncx-co / ifm_deferred_harvest

Documents, Data, and Code. The NCX Methodology For Improved Forest Management (IFM) Through Short-Term Harvest Deferral.
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Public Comment: 187 (Ben Parkhurst) #187

Closed ncx-gitbot closed 1 year ago

ncx-gitbot commented 1 year ago

Commenter Organization: Bluesource LLC

Commenter: Ben Parkhurst

2021 Deferred Harvest Methodology Section: 11

Comment: We would like to advocate to make the baseline quantification methodology as clear as possible to ensure parity across projects developed by different project proponents. Similar to other IFM methodologies, there should be a clear step-by-step process with and example models on how projects should be implemented so that there is no ambiguity. In addition, there needs to be more explicit and replicable guidelines on how the baseline quantification should be verified to ensure projects are held to consistent verification standards.

Proposed Change: No Proposed Change

ncx-gitbot commented 1 year ago

NCX response: The business as usual model is a hierarchical statistical model that predicts one-year harvest risk and intensity based on FIA training data and a suite of covariates that include geographic, biological, economic, and sociological factors. Partial pooling across forest types ensures that the model is able to leverage the similarity and ubiquity of covariate relationships across the forests of the continental U.S. while still allowing for regionally specific differences. We appreciate comments noting that the structure and performance of the baseline model used within this methodology is strongly influential on the predicted and realized climate impact of projects. Our revised methodology increases transparency rather than following an expert review process. This includes both detailed documentation of particular models used, as well as sharing benchmarking and performance information for baseline models. Finally, the revised approach to uncertainty explicitly accounts for imprecision in the baseline model in calculating the final number of credits generated from projects developed under this methodology.