Impacts of Increasing Bioenergy Production on Timber Harvest and Carbon Emissions

2019 ◽  
Vol 34 (3-4) ◽  
pp. 311-335 ◽  
Author(s):  
Jinggang Guo ◽  
Peichen Gong ◽  
Runar Brännlund
2011 ◽  
Vol 41 (6) ◽  
pp. 1319-1332 ◽  
Author(s):  
Jean-François Carle ◽  
David A. MacLean ◽  
Thom A. Erdle ◽  
Roger J. Roy

About 70% (110 PJ) of energy used in New Brunswick is sourced from fossil fuels, and its high cost and uncertain long-term supply have renewed interest in bioenergy production. To evaluate opportunities for sourcing bioenergy from the forest, we integrated bioenergy and timber production into a forest estate model and evaluated joint production scenarios for 3.3 million hectares of Crown land in New Brunswick over a 100-year horizon. Scenarios included maximizing timber or bioenergy production under three timing preferences (expressed as discount rates) and various combinations of harvest residues, pulpwood biomass, and willow ( Salix spp.) plantations. Under scenarios that allocated 66% of harvest residues and 30% of pulpwood to bioenergy production, maximizing discounted (8%) timber or bioenergy, respectively, generated average timber harvests of 6.51 and 6.26 Mm3·year–1 and bioenergy outputs equivalent to 30% and 32% of provincial fossil fuel consumption. Introducing 40 000 ha of willow plantations under the maximize bioenergy scenario yielded bioenergy equivalent to 41% of provincial fossil fuel consumption while maintaining the timber harvest at 6.21 Mm3·year–1. Our study demonstrates a framework for integrating bioenergy and timber production in forest management design and quantifies the significant potential for obtaining both bioenergy and timber from the forest.


Forests ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 277
Author(s):  
Eszter Sántha ◽  
Niclas Scott Bentsen

Research highlights: The study enabled us to quantitatively assess ecosystem benefits and trade-offs, to characterize species as generalists or specialists, and findings suggest that producing biomass for energy is more likely to serve multiple objectives if it is implemented in an integrated production system. Background and Objectives: Biomass is one of the main and largest sources of renewable energy. In Denmark, the production of biomass for energy is mainly based on timber harvest residues from pre-commercial thinning of forest stands. However, there is an increasing demand for bioenergy that require biomass to be grown specifically for energy purposes even though the sustainability and climate change mitigation potential of bioenergy plantations have recently been questioned in terms of food production, land use, land use change and terrestrial carbon cycles. The overall objective of the research is to better understand the opportunities and trade-offs between different woody and non-woody energy crops. Material and Methods: This study assessed the ecosystem services of seven woody species and one perennial along a management intensity continuum with a main focus on bioenergy production. Results: Results of the analysis showed that there are complex interrelations between ecosystem services and significant differences between species in providing those services. Conclusions: Species with a highest energy benefit among assessed species were poplar and grand fir, while beech and oak proved the best in providing biodiversity benefits.


Forests ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1307
Author(s):  
Sandra Brown ◽  
Abu R. J. Mahmood ◽  
Katherine M. Goslee ◽  
Timothy R. H. Pearson ◽  
Hansrajie Sukhdeo ◽  
...  

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.


2018 ◽  
Author(s):  
Chyi Lee ◽  
Hanlu Fan ◽  
QingLiang Tang ◽  
Peddy Lai

2014 ◽  
Author(s):  
Erik C. Berg ◽  
Charles B. Gale ◽  
Todd A. Morgan ◽  
Allen M. Brackley ◽  
Charles E. Keegan ◽  
...  

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