# Title of Dataset --- Root functional traits determine the magnitude of the rhizosphere priming effect among eight tree species. ## Description of the data and file structure Figure 1 Change in CO2 efflux from microcosms induced by eight plant species along 204 days of growth. CO2 efflux from an unplanted control (black lines with squares), as well as the total CO2 (red lines with circles), soil-derived CO2 (blue lines with triangles), plant-derived CO2 (pink lines with inverted triangles) and priming of SOC (green lines with diamonds) induced by plants are represented for each species. Values are mean ± SE. Figure 2 Mean daily (a) soil organic matter (SOM-)derived CO2, plant-derived CO2 and CO2 associated to the primed C (data above the bars), (b) rhizosphere priming effect, and (c) root exudate-derived CO2 along the 204 days of growth in planted treatments. Sub-legend shows ANOVA P values. Values are mean ± SE; n=5 for all treatments except for n=4 for Quercus acutissima, Carya cathayensis and Schima superba treatments. Figure 3 Relationships between the rhizosphere priming effect and (a) mean first-order root diameter, (b) root branching density, and (c) root exudate-derived respiration. The means of each species are plotted and error bars represent±SE; n=5 for all treatments except for n=4 for Quercus acutissima, Carya cathayensis and Schima superba treatments. Strength (R2) and significance (P) of linear regressions are displayed when (marginally-) significant. The filled areas indicate the 95% confidence interval. ## Sharing/Access information This is a section for linking to other ways to access the data, and for linking to sources the data is derived from, if any. Links to other publicly accessible locations of the data: * Data was derived from the following sources: * ## Code/Software This is an optional, freeform section for describing any code in your submission and the software used to run it. Describe any scripts, code, or notebooks (e.g., R, Python, Mathematica, MatLab) as well as the software versions (including loaded packages) that you used to run those files. If your repository contains more than one file whose relationship to other scripts is not obvious, provide information about the workflow that you used to run those scripts and notebooks.