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2017 | OriginalPaper | Chapter

7. Role of Forest Service Data and Methodologies

Authors : Eric Marland, Grant Domke, Jason Hoyle, Gregg Marland, Laurel Bates, Alex Helms, Benjamin Jones, Tamara Kowalczyk, Tatyana B. Ruseva, Celina Szymanski

Published in: Understanding and Analysis: The California Air Resources Board Forest Offset Protocol

Publisher: Springer International Publishing

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Abstract

Calculating forest offset credits under the California Forest Offset Protocol is heavily dependent on data from the U.S. Forest Service (USFS) and on methodologies developed by the USFS. The USFS data include both archived data and continuing data compilations. They include both published and unpublished data. The driving data source for calculating forest offset credits is, in fact, the U.S. Forest Service. The Forest Inventory and Analysis (FIA) program (USDA Forest Service 2016) within the Forest Service, employs a multi-phase inventory of U.S. forest attributes, with each phase contributing to the subsequent phase. To quote from the FIA web site: “The Forest Inventory and Analysis (FIA) Program of the U.S. Forest Service provides the information needed to assess America’s forests. As the Nation’s continuous forest census, our program projects how forests are likely to appear 10 to 50 years from now. This enables us to evaluate whether current forest management practices are sustainable in the long run and to assess whether current policies will allow the next generation to enjoy America’s forests as we do today. FIA reports on status and trends in forest area and location; in the species, size, and health of trees; in total tree growth, mortality, and removals by harvest; in wood production and utilization rates by various products; and in forest land ownership.” USFS historic and continuing data and methods compilations are integral to the calculations in the ARB offset protocol and many are directly linked from the California Air Resources Board web site (California ARB 2015a).

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Metadata
Title
Role of Forest Service Data and Methodologies
Authors
Eric Marland
Grant Domke
Jason Hoyle
Gregg Marland
Laurel Bates
Alex Helms
Benjamin Jones
Tamara Kowalczyk
Tatyana B. Ruseva
Celina Szymanski
Copyright Year
2017
DOI
https://doi.org/10.1007/978-3-319-52434-4_7