Scaling up of peatland methane emission hotspots from small to large scales
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Date
15//2/26/1Item status
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00//2/31/1Author
Mohammed, Abdulwasey
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Abstract
Methane is an important greenhouse gas that is relatively long-lived in the atmosphere, and
wetlands are a major natural source of atmospheric methane. Methane emissions from
wetlands are variable across both space and time at scales ranging from meters to continents
and a comprehensive accounting of wetland methane efflux is critical for quantifying the
atmospheric methane balance. Major uncertainties in quantifying methane efflux arise when
measuring and modelling its physical and biological determinants, including water table depth,
microtopography, soil temperature, the distribution of aerenchymous vegetation, and the
distribution of mosses. Further complications arise with the nonlinear interaction between flux
and derivers in highly-heterogeneous wetland landscape. A possible solution for quantifying
wetland methane efflux at multiple scales in space (‘upscaling’) is repeated observations using
remote sensing technology to acquire information about the land surface across time, space,
and spectra. These scaling issues must be resolved to progress in our understanding of the role
of wetlands in the global atmospheric methane budget from peatlands.
In this thesis, data collected from multiple aircraft and satellite-based remote sensing platforms
were investigated to characterize the fine scale spatial heterogeneity of a peatland in southwestern
Scotland for the purpose of developing techniques for quantifying (‘upscaling’)
methane efflux at multiple scales and space.
Seasonal variation in pools such as expansion and contraction was simulated with the LiDAR
data to investigate the expansion and contraction of the lakes and pools that could give an idea
of increase or decrease in methane emissions.
Concepts from information theory applied on the different data sets also revealed the relative
loss in some features on peatland surface and relative gain on others and find a natural
application for reducing bias in multi-scale spatial classification as well as quantifying the length
scales (or scales) at which important surface features for methane fluxes are lost.
Results from the wavelet analysis demonstrated the preservation of fine scale heterogeneity up
to certain length scale and the pattern on peatland surface was preserved. Variogram
techniques were also tested to determine sample size, range and orientation in the data set. All
the above has implications on estimating methane budget from the peatland landscape and
could reduce the bias in the overall flux estimates. All the methods used can also be applied to
contrasting sites.