USING PHYSICAL PRINCIPLES TO ENHANCE THE MEASUREMENT, INTERPRETATION AND UNDERSTANDING OF SOIL RESPIRATION
Abstract
Atmospheric concentrations of greenhouse gases (GHGs) play an extremely important
role in regulating Earth’s climate system. Researchers need to understand how GHGs
are produced at a process-level in order to predict what might happen under future
climate scenarios. A great deal of work has gone into understanding the fundamental
processes that control GHG production and consumption, but many questions remain.
To date, much of this research has focused on the biology of the soil system but there
are also many physical processes that control the transport of decomposable substrate,
nutrient supply, the local-environment (e.g. temperature and moisture) as well as the
eventual emission of GHGs to the atmosphere (i.e. diffusion and advection). Some
recent soil respiration studies suggest that the physical aspects of the soil have an
equal or greater influence on the measurement and interpretation of soil respiration
data.
Here a combination of numerical and analytical models, laboratory experiments
and field studies are used to help understand the effect that soil physics has on the
measurement and interpretation of soil respiration data. These analyses focus mainly
on high-resolution and istopologue techniques for understanding soil respiration, and
how considerations including gas diffusion and thermal conduction affect results
obtained using these methods. The interpretation of soil respiration data is also
carefully considered, again with a focus on how physical drivers can explain patterns in
field measurements, and how physical and biological processes might be disentangled
in GHG investigations. The results presented here show clearly how gaseous diffusion,
thermal conduction and poor methodological assumptions can bias the measurement
and interpretation of GHG emissions data. These biases and misinterpretations
can often be resolved through application of physical principles and mathematical
modelling. The physical and mathematical approaches presented here form a basis
for making robust measurements of GHG emissions and also for forming process-based
models that can be more universally applicable across space and time.