Sandra Brown
Accounting for Greenhouse Gas Emissions from Forest Edge Degradation: Gold Mining in Guyana as a Case Study
Brown, Sandra; Mahmood, Abu R.J.; Goslee, Katherine M.; Pearson, Timothy R.H.; Sukhdeo, Hansrajie; Donoghue, Daniel N.M.; Watt, Pete
Authors
Abu R.J. Mahmood
Katherine M. Goslee
Timothy R.H. Pearson
Hansrajie Sukhdeo
Professor Daniel Donoghue danny.donoghue@durham.ac.uk
Professor
Pete Watt
Abstract
Background and Methods: Degradation of forests in developing countries results from multiple activities and is perceived to be a key source of greenhouse gas emissions, yet there are not reliable methodologies to measure and monitor emissions from all degrading activities. Therefore, there is limited knowledge of the actual extent of emissions from forest degradation. Degradation can be either in the forest interior, with a repeatable defined pattern within areas of forest, as with timber harvest, or on the forest edge and immediately bounding areas of deforestation. Forest edge degradation is especially challenging to capture with remote sensing or to predict from proxy factors. This paper addresses forest edge degradation and: (1) proposes a low cost methodology for assessing forest edge degradation surrounding deforestation; (2) using the method, provides estimates of gross carbon emissions from forest degradation surrounding and caused by alluvial mining in Guyana, and (3) compares emissions from mining degradation with other sources of forest greenhouse gas emissions. To estimate carbon emissions from forest degradation associated with mining in Guyana, 100 m buffers were located around polygons pre-mapped as mining deforestation, and within these buffers rectangular transects were established. Researchers collected ground data to produce estimates of the biomass damaged as a result of mining activities to apply to the buffer area around the mining deforestation. Results: The proposed method to estimate emissions from forest edge degradation was successfully piloted in Guyana, where 61% of the transects lost 10 Mg C ha−1 or less in trees from mining damage and 46% of these transects lost 1 Mg C ha−1 or less. Seventy percent of the damaged stems and 60% of carbon loss occurred in the first 50 m of the transects. The median loss in carbon stock from mining damage was 2.2 Mg C ha−1 (95% confidence interval: 0.0–10.2 Mg C ha−1). The carbon loss from mining degradation represented 1.0% of mean total aboveground carbon stocks, with emissions from mining degradation equivalent to ~2% of all emissions from forest change in Guyana. Conclusions: Gross carbon emissions from forest degradation around mining sites are of little significance regardless of persistence and potential forest recovery. The development of cost- and time-effective buffers around deforestation provides a sound approach to estimating carbon emissions from forest degradation adjacent to deforestation including surrounding mining. This simple approach provides a low-cost method that can be replicated anywhere to derive forest degradation estimates.
Citation
Brown, S., Mahmood, A. R., Goslee, K. M., Pearson, T. R., Sukhdeo, H., Donoghue, D. N., & Watt, P. (2020). Accounting for Greenhouse Gas Emissions from Forest Edge Degradation: Gold Mining in Guyana as a Case Study. Forests, 11(12), Article 1307. https://doi.org/10.3390/f11121307
Journal Article Type | Article |
---|---|
Acceptance Date | Dec 4, 2020 |
Online Publication Date | Dec 7, 2020 |
Publication Date | 2020-12 |
Deposit Date | Dec 8, 2020 |
Publicly Available Date | Dec 8, 2020 |
Journal | Forests |
Electronic ISSN | 1999-4907 |
Publisher | MDPI |
Peer Reviewed | Peer Reviewed |
Volume | 11 |
Issue | 12 |
Article Number | 1307 |
DOI | https://doi.org/10.3390/f11121307 |
Public URL | https://durham-repository.worktribe.com/output/1255890 |
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Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/
Copyright Statement
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).
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