Complexity, global climate change and soil carbon cycling: Factors controlling the temperature response of microbial decomposition

Devin Wixon

Abstract


A proliferation of data being gathered to predict a critically important, urgent and social-policy related question leads only to confusion, debate and paralysis. This classic feature of complex systems is currently being evidenced in answering the question of a positive feedback response of soil respiration with increased temperatures due to global climate change. As with many current environmental challenges, a web of confounding factors acting at different scales complicate the integration of the results into a clear narrative. This is a strikingly complex system, and debate rages regarding even seemingly basic questions.
However, agreeing that this is a problem has not led to a solution. In particular, a comprehensive explanation of what factors are problematic is lacking. This research applies soft systems modeling (SSM) to the question: Why can’t we satisfactorily answer the question? My first conclusion from a review of the literature is that varied perspectives on the system’s dynamics and its web of controlling factors have led to seemingly conflicting results. At different levels of analysis, different constraints apply. Models must compress information and select driving factors of interest, but they must also account for the integrated effects of factors that are not explicitly included. The microbial community functions as a holon, and has been compressed to its outputs in most temperature response research. New technologies, however, are effectively providing insight into micro-scale dynamics. Experimental design, model development, and their integration can benefit from a holistic, systems approach to the diverse perspectives and associated factors of interest. The intent is not to theoretically assert that there are different points of view but rather to explicitly identify them and their associated system boundaries. This culminates at the end of step two in a first conceptual model of the potential universe of factors under discussion across perspectives. This model is organized in a hierarchy of levels and categories. Step three involves looking in general at the factors, and illustrates definitions based in distinct system abstractions. I present a simplified hierarchy (a “holarchy”) implemented as a relational database, including relationships between factors such as subset elements (nesting and feedbacks. I conclude that although this model is limited to pairwise interactions, it provides a useful tool to assess potential interactions and factors of interest

Keywords


Soft systems modeling, hierarchy theory, microbial decomposition, global climate change, systems biology, environmental modeling

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