Improving the Combustion Factor to Estimate GHG Emissions Associated with Fire in Pinus radiata and Eucalyptus spp. Plantations in Chile

Author:

Olmedo Guillermo Federico1ORCID,Gilabert Horacio2ORCID,Bown Horacio3,Sanhueza Rebeca4,Silva Pía5,Jorquera-Stuardo Carlos1,Sierra Francisco5

Affiliation:

1. Investigaciones Forestales Bioforest S.A., Camino a Coronel, Km. 15, Concepción 403 0000, Chile

2. Centro Interdisciplinario de Cambio Global, Pontificia Universidad Católica de Chile, Av. Vicuña Mackenna 4860, Santiago 782 0436, Chile

3. Facultad de Ciencias Forestales y de la Conservación de la Naturaleza, Universidad de Chile, Casilla 9206, Santiago 103 0000, Chile

4. Empresas CMPC S.A., Agustinas 1343, Santiago 103 0000, Chile

5. Corporación Chilena de la Madera A.G. (CORMA), Agustinas 1357 Piso, 3, Santiago 103 0000, Chile

Abstract

Forest plantations can substantially contribute to carbon sequestration and greenhouse gas (GHG) mitigation at the country and global scales. Forest fires (especially when combined with droughts) may remarkably reduce such carbon sequestration capability. The IPCC has global-scale estimates for such losses, but they can vary widely depending on crops, climate, topography, and management, among other factors. The IPCC defines a factor for biomass loss as a consequence of forest fires, expressed as a fraction of total biomass. This methodology implies using aggregated data and the default emission factor, which are only recommended for countries where wildfires are not a key category. In Chile, over the last decade, there have been between 5000 and 8000 wildfires annually (an average of 6398 for the period 2011–2020), burning an average of 122,328 hectares each year. Countries may progress in the refinement of such factors depending on the availability and reliability of local values. This paper aims at estimating Cf values for the main forest plantation species in Chile, Pinus radiata, Eucalyptus nitens, and Eucalyptus globulus, across different age-classes and forest fire severity. To achieve this aim, we assessed the biomass loss after forest fires for a stratified sample of forest plots for the season 2018–2019. We fitted a model to predict the amount of biomass loss during fires, and in this way, predict the emissions associated with wildfires. The model employs very simple predictive variables, age and species, because statistics for burnt areas in plantations are only provided by age-classes and species, without details about productivity or management.

Publisher

MDPI AG

Subject

Forestry

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