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carbon ForGATE.R

Version 2 2023-12-05, 20:43
Version 1 2023-05-25, 15:08
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posted on 2023-12-05, 20:43 authored by Michelle L. Brown, Charles CanhamCharles Canham, Thomas Buccholz, John S. Gunn, Therese Donovan

R code used in: Brown, M. L., Canham, C. D., Murphy, L., and Donovan, T. M.. 2018. Timber harvest as the predominant disturbance regime in northeastern U.S. forests: effects of harvest intensification. Ecosphere 9(3):e02062.

Abstract:

U.S. forests, particularly in the eastern states, provide an important offset to greenhouse gas (GHG) emissions. Some have proposed that forest-based natural climate solutions can be strengthened via a number of strategies, including increases in production of forest biomass energy. We used output from a forest dynamics model [SORTIE-ND] in combination with a greenhouse gas accounting tool [ForGATE] to estimate the carbon consequences of current and intensified timber harvest regimes in the northeastern U.S. We considered a range of carbon pools including forest ecosystem pools, forest product pools, and waste pools, along with different scenarios of feedstock production for biomass energy. The business as usual (BAU) scenario, which represents current harvest practices derived from analysis of U.S. Forest Service Forest Inventory and Analysis data, sequestered more net CO2 equivalents than any of the intensified harvest and feedstock utilization scenarios over the next decade, the most important time period for combatting climate change. Increasing the intensity of timber harvest increased total emissions and reduced landscape average forest carbon stocks, resulting in reduced net carbon sequestration relative to current harvest regimes. Net carbon sequestration “parity points,” where the regional cumulative net carbon sequestration from alternate intensified harvest scenarios converge with and then exceed the business as usual baseline, ranged from 12 to 40 years. A “no harvest” scenario provides an estimate of an upper bound on forest carbon sequestration in the region given the expected successional dynamics of the region’s forests, but ignores leakage. Regional net carbon sequestration is primarily influenced by (i) the harvest regime and amount of forest biomass removal, (ii) the degree to which bioenergy displaces fossil fuel use, and (iii) the proportion of biomass diverted to energy feedstocks versus wood products. 

File list:

Carbon ForGATE.R  - this is the main file – takes input from the “load data.R” code and calculates all of the terms in the carbon sequestration model.  All the rest of the files are called as source code from within this file.

Constants and initializations.R – contains constants and initializes all dynamic variables for a new run of the model.

Default decay rates.R – contains default decay rates for various carbon pools.

Feedstock utilization scenarios.R – defines the proportions of harvested biomass used as different types of biomass energy feedstocks in the various scenarios available in the model.

Load data.R – code to load the SORTIE-ND output Rdata objects generated by Brown et al. (2018).

Product transfer coefficients.R – coefficients that define the flow of carbon between the various harvested wood products pools.

Scenario graphs.R – code to generate graphs at the end of a model run. 

Additional 210 R data files contain output for the individual carbon pools and forest products from the SORTIE-ND model simulations described in the paper.  The data files are used in the calculation of net carbon sequestration using the Carbon ForGATE model code.

Funding

Northeastern States Research Cooperative (NSRC)

History

Geographic description

Northern forest states of NY, VT, NH, ME.

Time period

2016, 2018

Methodology

Modeling net carbon sequestration of northern forests linking SORTIE-ND to a simplified detrital carbon dynamics model and a model of carbon dynamics of harvested wood products.

Taxonomic species or groups

Most common 30 northern forest tree species.

Secondary Data Contact

datamanagement@caryinstitute.org

Data Sharing Statement

The Cary Institute of Ecosystem Studies furnishes code and data under the following conditions: The code or data have received quality assurance scrutiny, and, although we are confident of their accuracy, Cary Institute will not be held liable for errors in the code or data. Code and data are subject to change resulting from updates in data screening or models used. To cite code or data, click on the Cite button on this page.

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