Multivariate Conditional Granger Causality Analysis for Lagged Response of Soil Respiration in a Temperate Forest

摘要: Ecological multivariate systems offer a suitable data set on which to apply recent advances in information theory and causality detection. These are driven by the interplay of various environmental factors: meteorological hydrological forcing, often correlated with each other at different time lags; biological factors, primary producers decomposers both autonomous coupled dynamics. Here, using conditional spectral Granger causality, we quantify directional causalities complex atmosphere-plant-soil system involving carbon cycle. is statistical approach, originating econometrics, used identify presence linear causal interactions between series data, based prediction theory. We first test see if there was significant difference structure among two treatments where allocation roots interrupted girdling. then expanded analysis, introducing radiation soil moisture. The results showed pattern multilevel interactions, some these depending upon number variables system. However, no differences emerged above below ground cycle treatments.