Non-growing season carbon emissions in a northern peatland are projected to increase under global warming

被引:25
作者
Rafat, Arash [1 ,2 ,3 ]
Rezanezhad, Fereidoun [2 ,3 ]
Quinton, William L. [4 ]
Humphreys, Elyn R. [5 ]
Webster, Kara [6 ]
Van Cappellen, Philippe [2 ,3 ]
机构
[1] Univ Waterloo, Dept Civil & Environm Engn, Waterloo, ON, Canada
[2] Univ Waterloo, Dept Earth & Environm Sci, Ecohydrol Res Grp, Waterloo, ON, Canada
[3] Univ Waterloo, Water Inst, Waterloo, ON, Canada
[4] Wilfrid Laurier Univ, Cold Reg Res Ctr, Waterloo, ON, Canada
[5] Carleton Univ, Dept Geog & Environm Studies, Ottawa, ON, Canada
[6] Nat Resources Canada, Canadian Forest Serv, Great Lakes Forestry Ctr, Sault Ste Marie, ON, Canada
来源
COMMUNICATIONS EARTH & ENVIRONMENT | 2021年 / 2卷 / 01期
基金
加拿大自然科学与工程研究理事会;
关键词
WINTER SOIL RESPIRATION; SENSITIVITY-ANALYSIS; ORGANIC-CARBON; CLIMATE-CHANGE; CO2; FLUX; DIFFERENT ECOSYSTEMS; PERMAFROST THAW; SNOW DEPTH; EXCHANGE; TEMPERATURE;
D O I
10.1038/s43247-021-00184-w
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Peatlands are important ecosystems that store approximately one third of terrestrial organic carbon. Non-growing season carbon fluxes significantly contribute to annual carbon budgets in peatlands, yet their response to climate change is poorly understood. Here, we investigate the governing environmental variables of non-growing season carbon emissions in a northern peatland. We develop a support-vector regression model using a continuous 13-year dataset of eddy covariance flux measurements from the Mer Blue Bog, Canada. We determine that only seven variables were needed to reproduce carbon fluxes, which were most sensitive to net radiation above the canopy, soil temperature, wind speed and soil moisture. We find that changes in soil temperature and photosynthesis drove changes in net carbon flux. Assessing net ecosystem carbon exchange under three representative concentration pathways, we project a 103% increase in peatland carbon loss by 2100 under a high emissions scenario. We suggest that peatland carbon losses constitute a strong positive climate feedback loop. Future changes in non-growing season conditions, particularly irradiance and temperature, will enhance carbon emissions from a northern peatland, according to projections with a data-driven machine learning model.
引用
收藏
页数:12
相关论文
共 118 条
[1]   Sensitivity of soil respiration and microbial communities to altered snowfall [J].
Aanderud, Zachary T. ;
Jones, Stuart E. ;
Schoolmaster, Donald R., Jr. ;
Fierer, Noah ;
Lennon, Jay T. .
SOIL BIOLOGY & BIOCHEMISTRY, 2013, 57 :217-227
[2]  
[Anonymous], 1963, INFLUENCE SNOW COVER
[3]  
Awad M., 2015, Efficient learning machines: Theories, concepts, and applications for engineers and system designers p, P67, DOI [10.1007/978-1-4302-5990-94, DOI 10.1007/978-1-4302-5990-9_4]
[4]   The changing seasonal climate in the Arctic [J].
Bintanja, R. ;
van der Linden, E. C. .
SCIENTIFIC REPORTS, 2013, 3
[5]   Carbon turnover in peatland mesocosms exposed to different water table levels [J].
Blodau, C ;
Basiliko, N ;
Moore, TR .
BIOGEOCHEMISTRY, 2004, 67 (03) :331-351
[6]   Random forests [J].
Breiman, L .
MACHINE LEARNING, 2001, 45 (01) :5-32
[7]   Fine-scale vegetation distribution in a cool temperate peatland [J].
Bubier, Jill L. ;
Moore, Tim R. ;
Crosby, Gareth .
CANADIAN JOURNAL OF BOTANY-REVUE CANADIENNE DE BOTANIQUE, 2006, 84 (06) :910-923
[8]   Prediction and analysis of net ecosystem carbon exchange based on gradient boosting regression and random forest [J].
Cai, Jianchao ;
Xu, Kai ;
Zhu, Yanhui ;
Hu, Fang ;
Li, Liuhuan .
APPLIED ENERGY, 2020, 262
[9]   Arctic loses carbon as winters wane [J].
Campbell, John L. .
NATURE CLIMATE CHANGE, 2019, 9 (11) :806-807
[10]   Bias Correction of GCM Precipitation by Quantile Mapping: How Well Do Methods Preserve Changes in Quantiles and Extremes? [J].
Cannon, Alex J. ;
Sobie, Stephen R. ;
Murdock, Trevor Q. .
JOURNAL OF CLIMATE, 2015, 28 (17) :6938-6959