Global warming, increasing CO 2 concentration, and environmental disturbances affect grassland communities throughout the world. Here, we report on variations in the C3/C4 pattern of Inner Mongolian grassland derived from soil and vegetation. Soil samples from 149 sites covering an area of approximately 250 000 km 2 within Inner Mongolia, People's Republic of China were analyzed for the isotopic composition (d 13 C) of soil organic carbon (SOC). The contrast in d 13 C between C3 and C4 plants allowed for calculation of the C3/C4 ratio from d 13 C of SOC with a two-member mixing model, which accounted for influences of aridity and altitude on d 13 C of the C3 end-member and for changes in d 13 C of atmospheric CO 2 . Maps were created geostatistically, and showed a substantially lower C4 abundance in soil than in recent vegetation (À10%). The difference between soil and vegetation varied regionally and was most pronounced within an E-W belt along 441N and in a mountainous area, suggesting a spread of C4 plants toward northern latitudes (about 11) and higher altitudes. The areas of high C4 abundance for present vegetation and SOC were well delineated by the isotherms of crossover temperature based on the climatic conditions of the respective time periods. Our study indicates that change in the patterns of C3/C4 composition in the Inner Mongolia grassland was mainly triggered by increasing temperature, which overrode the antagonistic effect of rising CO 2 concentrations.
Summary 1. Recently, Caut, Angulo & Courchamp (2009, Journal of Applied Ecology) published a review on diet‐tissue isotopic shifts in animals. They concluded that diet‐tissue shifts are influenced by the isotopic composition of the diet for both 13C and 15N in a wide range of animal taxa. 2. We suggest that the conclusion of Caut, Angulo & Courchamp is in error, and provide a discussion of sources of error in the assessment of diet‐tissue discrimination. 3. Errors in the derivation of diet‐tissue shifts include imprecise definitions, mathematical artefacts and invalid statistical analysis. It is likely that the work also suffers from experimental bias. The mathematical artefacts and statistical invalidity result from using the same variable (diet isotopic composition) in the independent and dependent variable for regression analysis and failure to correct for the resulting bias. Experimental bias can result from the incomplete turnover of body pools after diet switches or during natural fluctuations in diet isotope composition. Unfortunately, the main sources of error work in the same direction, strengthening the biased relationship between the diet‐tissue shift and diet isotope composition. Therefore, the analysis of Caut et al. (2009) does not provide proof of a relationship between diet‐tissue shift and diet isotope composition. 4. Synthesis and application. Future work on diet‐tissue discrimination factors should (i) follow the mathematical rules resulting from how isotope data are presented, (ii) be based on appropriate statistics analysis that avoids or corrects for spurious self‐correlations, and (iii) consider possible complications associated with the presence of slowly turning‐over stores and non‐equilibrating ‘dead’ body pools.
Abstract. The relationship between carbon isotope discrimination (13Δ) of C3 vegetation and long-term (30 years) and short-term (growing period) precipitation was investigated. Different species of Stipa, a dominant grass genus in the (semi-)arid Asian steppes, and other C3 species were collected along aridity gradients in Inner Mongolia in 2005 (11 sites, 71 samples) and in the Republic of Mongolia in 2006 (40 sites, 45 samples). The data set was expanded with published and unpublished data of Stipa and other C3 species (11 studies covering 8 years, including 64 observations of Stipa, and 103 observations of other C3 species) and C3 community bulk-samples (11 samples). Weather data were geostatistically interpolated for all sampling sites and years. 13Δ of Stipa followed different relationships for the individual years when related to mean annual precipitation due to large anomalies between annual and long-term average precipitation patterns. However, the 13Δ response to rainfall converged when the (long-term) mean annual precipitation was replaced by year-specific mean daily precipitation during the growing period (PG). Remarkably, the 13Δ-response to (PG) for C3 species as a whole (including herbaceous dicots, semi-shrubs and grasses) and also the C3 community-level response were virtually identical to that of Stipa. The relation was also valid outside the geographical and climatic range where it was developed, giving proof of its robustness.
Abstract. This work explored the spatial variation of C3/C4 distribution in the Inner Mongolia, China, steppe by geostatistical analysis of carbon isotope data of vegetation and sheep wool. Standing community biomass (n=118) and sheep wool (n=146) were sampled in a ~0.2 Mio km2 area. Samples from ten consecutive years (1998–2007) were obtained. Community biomass samples represented the carbon isotopic composition of standing vegetation on about 1000 m2 ("community-scale"), whereas the spatio-temporal scale of wool reflected the isotope composition of the entire area grazed by the herd during a 1-yr period (~5–10 km2, "farm-scale"). Pair wise sampling of wool and vegetation revealed a 13C-enrichment of 2.7‰ in wool relative to vegetation, but this shift exhibited no apparent relationships with environmental parameters or stocking rate. The proportion of C4 plants in above-ground biomass (PC4, %) was estimated with a two-member mixing model of C3 and C4 13C discrimination (13Δ3 and 13Δ4, respectively), in accounting for the effects of changing 13C in atmospheric CO2 on sample isotope composition, and of altitude and aridity on 13Δ3. PC4 averaged 19%, but the variation was enormous: full-scale (0% to 100%) at community-scale, and 0% to 85% at farm-scale. The farm-scale variation of PC4 exhibited a clear regional pattern over a range of ~250 km. Importantly PC4 was significantly higher above and lower below the 22°C isotherm of the warmest month, which was averaged from high-resolution maps of the sample years. This is consistent with predictions from C3/C4 crossover temperature of quantum yield in C3 and C4 plants. Still, temperature gradients accounted for only 10% of the farm-scale variation of PC4, indicating that additional factors control PC4 on this scale.
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