Abstract
Ecological multivariate systems offer a suitable data set on which to apply recent advances in information theory and causality detection. These systems are driven by the interplay of various environmental factors: meteorological and hydrological forcing, which are often correlated with each other at different time lags; and biological factors, primary producers and decomposers with both autonomous and coupled dynamics. Here, using conditional spectral Granger causality, we quantify directional causalities in a complex atmosphere-plant-soil system involving the carbon cycle. Granger causality is a statistical approach, originating in econometrics, used to identify the presence of linear causal interactions between time series of data, based on prediction theory. We first test to see if there was a significant difference in the causal structure among two treatments where carbon allocation to roots was interrupted by girdling. We then expanded the analysis, introducing radiation and soil moisture. The results showed a complex pattern of multilevel interactions, with some of these interactions depending upon the number of variables in the system. However, no significant differences emerged in the causal structure of above and below ground carbon cycle among the two treatments.
Highlights
The seasonal rate of change in atmospheric carbon dioxide (CO2) above temperate regions is largely driven by the net sum of two opposing processes: carbon (C) uptake through Gross PrimaryProduction (GPP) and carbon release from the vegetation and soil through plant and microbial respiration
The magnitude of the annual ecosystem-driven change to the global soil C pool is such that even a small increase in soil respiration (Rs) rates could result in a net reduction in net terrestrial C sink strength and an increase in atmospheric CO2 concentration [1,2,3]
Bivariate and conditional G-causalities on Gross PrimaryProduction (GPP) and Ts over Rs showed a large effect of temperature and a much smaller effect of GPP, especially at low frequencies (Figure 4)
Summary
The seasonal rate of change in atmospheric carbon dioxide (CO2) above temperate regions is largely driven by the net sum of two opposing processes: carbon (C) uptake through Gross PrimaryProduction (GPP) and carbon release from the vegetation and soil through plant and microbial respiration. The soil ecosystem comprises a multitude of organisms acting over a broad range of spatial and temporal scales, from heterotrophic soil fauna to plant roots, all embedded in a complex and highly variable physical environment [4]. This variation is both spatial, through differences in soil microbial communities and root structural characteristics, and temporal, through fluctuations in energy and water dynamics and through disturbances. A principal challenge to understanding biogeochemical cycles is identifying the causal agents of process rates, which requires separation of endogenous dynamics from the effects of the timedependent, and often correlated, forcing variables. Due to the symmetric nature of correlation it cannot distinguish between the causal roles of the affected and affecting variable
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