Vegetation and soil carbon‐13 isoscapes for South America: integrating remote sensing and ecosystem isotope measurements

摘要

The carbon isotope composition (δ~(13)C) of terrestrial vegetation and soils is required for a diverse set of research, including carbon cycle studies that utilize global atmospheric CO_(2) and δ~(13)C data, as well as studies of animal migration and food web dynamics where the δ~(13)C of plants and soils is imparted to animal tissues. We present δ~(13)C maps for South America that correspond roughly to the year 2000, based upon predictions of the abundance and distribution of C_(3) and C_(4) vegetation, along with empirical measures of the δ~(13)C of plant leaf and soil endmembers. Our approach relies upon the near‐universal restriction of C_(4) photosynthesis to the herbaceous growth form and the differing performance of C_(3) and C_(4) grasses in various climates, along with land‐cover and crop‐type distributions. Specifically, we predict the percentage cover of C_(3) and C_(4) vegetation in each 5‐minute grid cell (～10 km) based on input gridded layers of vegetation growth form fractional cover, crop‐area/crop‐type distributions, and a high spatial resolution climate data. We develop a consistent set of rules to harmonize the different data layers. The δ~(13)C of vegetation in South America is then estimated based on the C_(3)/C_(4) composition in each land grid cell, assuming constant mean values for closed C_(3) tropical forest (?32.3‰), open C_(3) forest ecosystems (?29.0‰), C_(3) herbaceous cover (?26.7‰) and C_(4) herbaceous cover (?12.5‰). In addition to using the mean isotope values, we also incorporate the measured standard deviation for each category. Soil δ~(13)C is estimated for the C_(4)‐favored climate regions of South America using two, largely independent approaches: one that is derived from our vegetation δ~(13)C prediction and one that is based on a previously published relationship between fractional woody cover and the δ~(13)C of soil organic carbon. Finally, we present preliminary maps of relative uncertainty in the estimates of vegetation growth form, generated by integrating global measures of accuracy with local measures of neighborhood variability. These maps demonstrate that the highest uncertainty is found in savanna ecosystems, which contain the most heterogeneous vegetation cover and structure along with a high percentage of C_(4) grass cover.