Measuring Heterotroph-Induced Source-Sink Relationships in Panicum Coloratum with ^1^1C Technology

We report a synthesis from three series of experiments on source-sink relationships in Panicum coloratum L., a C"4 tropical grass obtained from the Serengeti grasslands of Africa. Studies on ^1^1C real-time analyses of P. coloratum to determine aboveground effects of grasshopper grazing and belowground effects of mycorrhizal inoculation and nematode feeding provided the database. A series of multi- and univariate statistical investigations of all available experimental data described responses of leaves, stems, and roots to these biological stresses. From a principal components analysis we have shown differences in distribution of C source-sink locations along three principal component axes, which accounted for 84% of the experimental variance. The first and second components (62% of variance) described C allocation to leaf, stem, and root sinks. The third component (22% of variance) showed a metabolic dichotomy between leaf starch sinks and labile carbon pools throughout the plant. We use the three principal components from a ^1^1C three-compartment model describing leaf, stem, and root C source and sink variables to present patterns, or fingerprints, of responses to the experiments. Time of day, treatment class, number of days since transplanting, and ecotype controlled a large amount of the overall variation in plant C fixation and reallocation. A comparison of ^1^2C leaf carbon exchange rates (CER) measured with an infrared gas analyzer and ^1^1C rates showed a high positive correlation. Slopes for grasshopper grazing, mycorrhizal inoculation experiments, and nematode feeding showed almost identical results; however, differences in the intercept developed as a function of ecotype. We noted a significantly lower intercept in morning studies, but no differences in the slope for morning compared to afternoon studies. CER and all ^1^1C variables for grasshopper and nematode experiments showed a lower coefficient of ^1^1C variables and higher for CER. We conclude that ^1^1C experiments provide the base for developing laboratory, field, modeling studies to incorporate aggregations of real-time C transfers within plants responding to biological stresses, including those of heterotrophs.