4.7 Article

Estimating wetland methane emissions from the northern high latitudes from 1990 to 2009 using artificial neural networks

Journal

GLOBAL BIOGEOCHEMICAL CYCLES
Volume 27, Issue 2, Pages 592-604

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1002/gbc.20052

Keywords

methane emissions; northern wetlands; neural networks

Funding

  1. NASA [NASA-NNX09AI26G]
  2. Department of Energy [DE-FG02-08ER64599]
  3. NSF Division of Information and Intelligent Systems [NSF-1028291]
  4. NSF Carbon and Water in the Earth Program [NSF-0630319]
  5. Direct For Biological Sciences
  6. Division Of Environmental Biology [0919331] Funding Source: National Science Foundation
  7. Direct For Computer & Info Scie & Enginr
  8. Div Of Information & Intelligent Systems [1028291] Funding Source: National Science Foundation

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Methane (CH4) emissions from wetland ecosystems in nothern high latitudes provide a potentially positive feedback to global climate warming. Large uncertainties still remain in estimating wetland CH4 emisions at regional scales. Here we develop a statistical model of CH4 emissions using an artificial neural network (ANN) approach and field observations of CH4 fluxes. Six explanatory variables (air temperature, precipitation, water table depth, soil organic carbon, soil total porosity, and soil pH) are included in the development of ANN models, which are then extrapolated to the northern high latitudes to estimate monthly CH4 emissions from 1990 to 2009. We estimate that the annual wetland CH4 source from the northern high latitudes (north of 45 degrees N) is 48.7 (4) yr(-1) (1 (12)g) with an uncertainty range of 44.0 similar to 53.7 (4) yr(-1). (4) emissions show a large spatial variability over the northern high latitudes, due to variations in hydrology, climate, and soil conditions. Significant interannual and seasonal variations of wetland CH4 emissions exist in the past 2 decades, and the emissions in this period are most sensitive to variations in water table position. (4) dynamics in this region, research priorities should be directed to better characterizing hydrological processes of wetlands, including temporal dynamics of water table position and spatial dynamics of wetland areas.

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