Dataset Information

Spatially-integrated estimates of net ecosystem exchange and methane fluxes from Canadian peatlands.

ABSTRACT:

Background

Peatlands are an important component of Canada's landscape, however there is little information on their national-scale net emissions of carbon dioxide [Net Ecosystem Exchange (NEE)] and methane (CH₄). This study compiled results for peatland NEE and CH₄ emissions from chamber and eddy covariance studies across Canada. The data were summarized by bog, poor fen and rich-intermediate fen categories for the seven major peatland containing terrestrial ecozones (Atlantic Maritime, Mixedwood Plains, Boreal Shield, Boreal Plains, Hudson Plains, Taiga Shield, Taiga Plains) that comprise >?96% of all peatlands nationally. Reports of multiple years of data from a single site were averaged and different microforms (e.g., hummock or hollow) within these peatland types were kept separate. A new peatlands map was created from forest composition and structure information that distinguishes bog from rich and poor fen. National Forest Inventory k-NN forest structure maps, bioclimatic variables (mean diurnal range and seasonality of temperatures) and ground surface slope were used to construct the new map. The Earth Observation for Sustainable Development map of wetlands was used to identify open peatlands with minor tree cover.

Results

The new map was combined with averages of observed NEE and CH₄ emissions to estimate a growing season integrated NEE (±?SE) at -?108.8 (±?41.3) Mt CO₂ season^-1 and CH₄ emission at 4.1 (±?1.5) Mt CH₄ season^-1 for the seven ecozones. Converting CH₄ to CO₂ equivalent (CO₂e; Global Warming Potential of 25 over 100 years) resulted in a total net sink of -?7.0 (±?77.6) Mt CO₂e season^-1 for Canada. Boreal Plains peatlands contributed most to the NEE sink due to high CO₂ uptake rates and large peatland areas, while Boreal Shield peatlands contributed most to CH₄ emissions due to moderate emission rates and large peatland areas. Assuming a winter CO₂ emission of 0.9 g CO₂ m^-2 day^-1 creates an annual CO₂ source (24.2 Mt CO₂ year^-1) and assuming a winter CH₄ emission of 7 mg CH₄ m^-2 day^-1 inflates the total net source to 151.8 Mt CO₂e year^-1.

Conclusions

This analysis improves upon previous basic, aspatial estimates and discusses the potential sources of the high uncertainty in spatially integrated fluxes, indicating a need for continued monitoring and refined maps of peatland distribution for national carbon and greenhouse gas flux estimation.

SUBMITTER: Webster KL

PROVIDER: S-EPMC6147052 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Spatially-integrated estimates of net ecosystem exchange and methane fluxes from Canadian peatlands.

Webster K L KL Bhatti J S JS Thompson D K DK Nelson S A SA Shaw C H CH Bona K A KA Hayne S L SL Kurz W A WA

Carbon balance and management 20180920 1

<h4>Background</h4>Peatlands are an important component of Canada's landscape, however there is little information on their national-scale net emissions of carbon dioxide [Net Ecosystem Exchange (NEE)] and methane (CH<sub>4</sub>). This study compiled results for peatland NEE and CH<sub>4</sub> emissions from chamber and eddy covariance studies across Canada. The data were summarized by bog, poor fen and rich-intermediate fen categories for the seven major peatland containing terrestrial ecozone ...[more]

PMID: 30238271

Similar Datasets

Project description:Forests play a crucial role in the global carbon (C) cycle by storing and sequestering a substantial amount of C in the terrestrial biosphere. Due to temporal dynamics in climate and vegetation activity, there are significant regional variations in carbon dioxide (CO2) fluxes between the biosphere and atmosphere in forests that are affecting the global C cycle. Current forest CO2 flux dynamics are controlled by instantaneous climate, soil, and vegetation conditions, which carry legacy effects from disturbances and extreme climate events. Our level of understanding from the legacies of these processes on net CO2 fluxes is still limited due to their complexities and their long-term effects. Here, we combined remote sensing, climate, and eddy-covariance flux data to study net ecosystem CO2 exchange (NEE) at 185 forest sites globally. Instead of commonly used non-dynamic statistical methods, we employed a type of recurrent neural network (RNN), called Long Short-Term Memory network (LSTM) that captures information from the vegetation and climate's temporal dynamics. The resulting data-driven model integrates interannual and seasonal variations of climate and vegetation by using Landsat and climate data at each site. The presented LSTM algorithm was able to effectively describe the overall seasonal variability (Nash-Sutcliffe efficiency, NSE = 0.66) and across-site (NSE = 0.42) variations in NEE, while it had less success in predicting specific seasonal and interannual anomalies (NSE = 0.07). This analysis demonstrated that an LSTM approach with embedded climate and vegetation memory effects outperformed a non-dynamic statistical model (i.e. Random Forest) for estimating NEE. Additionally, it is shown that the vegetation mean seasonal cycle embeds most of the information content to realistically explain the spatial and seasonal variations in NEE. These findings show the relevance of capturing memory effects from both climate and vegetation in quantifying spatio-temporal variations in forest NEE.

Dataset Information

Spatially-integrated estimates of net ecosystem exchange and methane fluxes from Canadian peatlands.

Background

Results

Conclusions

Publications

Spatially-integrated estimates of net ecosystem exchange and methane fluxes from Canadian peatlands.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets