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加拿大安大略省北部森林的历史和未来碳储量。

Historical and future carbon stocks in forests of northern Ontario, Canada.

作者信息

Ter-Mikaelian Michael T, Gonsamo Alemu, Chen Jing M, Mo Gang, Chen Jiaxin

机构信息

Ontario Forest Research Institute, Ontario Ministry of Natural Resources and Forestry, 1235 Queen Street E., Sault Ste. Marie, ON, P6A 2E5, Canada.

School of Earth, Environment & Society, McMaster University, 1280 Main Street West, Hamilton, ON, L8S 4S4, Canada.

出版信息

Carbon Balance Manag. 2021 Jul 15;16(1):21. doi: 10.1186/s13021-021-00184-5.

Abstract

BACKGROUND

Forests in the Far North of Ontario (FNO), Canada, are likely the least studied in North America, and quantifying their current and future carbon (C) stocks is the first step in assessing their potential role in climate change mitigation. Although the FNO forests are unmanaged, the latter task is made more important by growing interest in developing the region's natural resources, primarily for timber harvesting. In this study, we used a combination of field and remotely sensed observations with a land surface model to estimate forest C stocks in the FNO forests and to project their future dynamics. The specific objective was to simulate historical C stocks for 1901-2014 and future C stocks for 2015-2100 for five shared socioeconomic pathway (SSP) scenarios selected as high priority scenarios for the 6th Assessment Report on Climate Change.

RESULTS

Carbon stocks in live vegetation in the FNO forests remained relatively stable between 1901 and 2014 while soil organic carbon (SOC) stocks steadily declined, losing about 16% of their initial value. At the end of the historical simulation (in 2014), the stocks were estimated at 19.8, 46.4, and 66.2 tCha in live vegetation, SOC, and total ecosystem pools, respectively. Projections for 2015-2100 indicated effectively no substantial change in SOC stocks, while live vegetation C stocks increased, accelerating their growth in the second half of the twenty-first century. These results were consistent among all simulated SSP scenarios. Consequently, increase in total forest ecosystem C stocks by 2100 ranged from 16.7 to 20.7% of their value in 2015. Simulations with and without wildfires showed the strong effect of fire on forest C stock dynamics during 2015-2100: inclusion of wildfires reduced the live vegetation increase by half while increasing the SOC pool due to higher turnover of vegetation C to SOC.

CONCLUSIONS

Forest ecosystem C stock estimates at the end of historical simulation period were at the lower end but within the range of values reported in the literature for northern boreal forests. These estimates may be treated as conservatively low since the area included in the estimates is poorly studied and some of the forests may be on peat deposits rather than mineral soils. Future C stocks were projected to increase in all simulated SSP scenarios, especially in the second half of the twenty-first century. Thus, during the projected period forest ecosystems of the FNO are likely to act as a C sink. In light of growing interest in developing natural resources in the FNO, collecting more data on the status and dynamics of its forests is needed to verify the above-presented estimates and design management activities that would maintain their projected C sink status.

摘要

背景

加拿大安大略省最北部的森林(FNO)可能是北美地区研究最少的森林,量化其当前和未来的碳(C)储量是评估其在缓解气候变化中潜在作用的第一步。尽管FNO森林未受管理,但由于对开发该地区自然资源(主要用于木材采伐)的兴趣日益浓厚,后一项任务变得更加重要。在本研究中,我们结合实地和遥感观测数据以及一个陆面模型来估算FNO森林的碳储量,并预测其未来动态。具体目标是模拟1901 - 2014年的历史碳储量以及2015 - 2100年的未来碳储量,针对被选为气候变化第六次评估报告高优先级情景的五个共享社会经济路径(SSP)情景。

结果

1901年至2014年期间,FNO森林中活植被的碳储量相对稳定,而土壤有机碳(SOC)储量稳步下降,损失了约16%的初始值。在历史模拟结束时(2014年),活植被、SOC和总生态系统库中的碳储量估计分别为19.8、46.4和66.2 tC/ha。2015 - 2100年的预测表明,SOC储量实际上没有显著变化,而活植被碳储量增加,在21世纪后半叶加速增长。所有模拟的SSP情景结果均一致。因此,到2100年,森林生态系统总碳储量增加幅度为2015年碳储量值的16.7%至20.7%。有和没有野火的模拟结果表明,野火对2015 - 2100年森林碳储量动态有强烈影响:纳入野火使活植被增加量减半,同时由于植被碳向SOC的周转率提高,SOC库增加。

结论

历史模拟期结束时森林生态系统碳储量估计值处于较低水平,但在北方针叶林文献报道值范围内。由于估计范围内的区域研究不足,且部分森林可能位于泥炭沉积物而非矿质土壤上,这些估计值可能被视为保守的低估值。预计在所有模拟的SSP情景中,未来碳储量都会增加,尤其是在21世纪后半叶。因此,在预测期内,FNO的森林生态系统可能会作为一个碳汇。鉴于对开发FNO自然资源的兴趣日益浓厚,需要收集更多关于其森林现状和动态的数据,以验证上述估计值,并设计能够维持其预测碳汇状态的管理活动。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e5da/8281711/69aefdd34553/13021_2021_184_Fig1_HTML.jpg

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