Understanding of carbon exchange between terrestrial ecosystems and the atmosphere can be improved through direct observations and experiments, as well as through modeling activities. Terrestrial biosphere models (TBMs) have become an integral tool for extrapolating local observations and understanding to much larger terrestrial regions. Although models vary in their specific goals and approaches, their central role within carbon cycle science is to provide a better understanding of the mechanisms currently controlling carbon exchange. Recently, the North American Carbon Program (NACP) organized several interim-synthesis activities to evaluate and inter-compare models and observations at local to continental scales for the years 2000-2005. Here, we compare the results from the TBMs collected as part of the regional and continental interim-synthesis (RCIS) activities. The primary objective of this work is to synthesize and compare the 19 participating TBMs to assess current understanding of the terrestrial carbon cycle in North America. Thus, the RCIS focuses on model simulations available from analyses that have been completed by ongoing NACP projects and other recently published studies. The TBM flux estimates are compared and evaluated over different spatial (1 degrees X 1 degrees and spatially aggregated to different regions) and temporal (monthly and annually) scales. The range in model estimates of net ecosystem productivity (NEP) for North America is much narrower than estimates of productivity or respiration, with estimates of NEP varying between 0.7 and 2.2 PgC yr(-1), while gross primary productivity and heterotrophic respiration vary between 12.2 and 32.9 PgCyr(-1) and 5.6 and 13.2 PgC yr(-1), respectively. The range in estimates from the models appears to be driven by a combination of factors, including the representation of photosynthesis, the source and of environmental driver data and the temporal variability of those data, as well as whether nutrient limitation is considered in soil carbon decomposition. The disagreement in current estimates of carbon flux across North America, including whether North America is a net biospheric carbon source or sink, highlights the need for further analysis through the use of model runs following a common simulation protocol, in order to isolate the influences of model formulation, structure, and assumptions on flux estimates. (C) 2012 Elsevier B.V. All rights reserved
In this work, the authors have evaluated ten different ionization chambers for the relative dosimetry of kilovoltage x-ray beams in the energy range of 50-280 kVp. Percentage depth doses in water and relative detector response (in Solid Water and in air) were measured for each of the x-ray beams studied using a number of chambers. Measured depth dose data were compared with Monte Carlo calculated depth doses using the EGSnrc Monte Carlo package and the BEAMnrc user code. The accuracy of the phase space files generated by BEAMnrc was verified by calculating the half-value layer and comparing with the measured half-value layer of each x-ray beam. The results indicate that the Advanced Markus, Markus, NACP, and Roos parallel plate ionization chambers were suitable for the measurement of depth dose data in this beam quality range with an uncertainty of less than 3%, including in the regions close to the water surface. While the relative detector response of the Farmer and scanning thimble chambers exhibited a better energy response, they were not suitable for depth dose measurements in the first 5 mm below the water surface with differences of up to 12% in the surface dose measurement for the 50 kVp x-ray beam. These differences were due to dose artifacts generated by the chamber size and the dose gradient. However, at depths greater than 5 mm, the Farmer and thimble scanning chambers gave uncertainties of less than 3% for the depth dose measurements for all beam energies. The PTW PinPoint 31006 chamber was found to give varying dose differences of up to 8% depending on the x-ray beam energy; this was attributed to the steel central electrode. The authors recommend that one of the parallel plate ionization chambers investigated be used to determine depth dose data for kilovoltage x-ray beams in the energy range studied and give correct dose information close to the surface and at depth in the water phantom.
Ecoenzymatic stoichiometry links microbial decomposition with nutrient mineralization and improves our understanding of nutrient cycling in terrestrial ecosystems. Microbial C:N:P acquisition in the topsoil converged at a ratio of 1:1:1 in global ecosystems. However, whether the ratio of microbial acquisition is stable in forest soils, and is applicable among different soil depths remain unknown. Based on large‐scale soil sampling in China's forests, we examined the patterns and environmental drivers of the eight most‐widely measured enzyme activities and the relevant stoichiometry. We found that the ratio of C:N:P acquisition significantly deviated from 1:1:1. The specific enzyme activities (normalized by SOC) did not change significantly with latitude except those for xylosidase and acid phosphatase. Similarly, only the C:P acquisition ratio increased with latitude. Vertically, the specific activities of C‐acquiring enzymes mainly increased, N‐acquiring enzymes decreased and P‐acquiring enzymes did not change with soil depth. Moreover, all ratios of microbial acquisition decreased, and the percentage of recalcitrant C increased significantly with increasing depth. Our study also showed that temperature and soil C:N ratio were the important factors in explaining the variations in specific enzyme activities and microbial nutrient acquisition, respectively. Our results indicated that no constant microbial C:N:P acquisition ratio can be widely recognized, and that SOC quality changed from labile to recalcitrant with depth. We highlight that depth‐dependent enzymatic processes should be considered in future SOC dynamic models. A free Plain Language Summary can be found within the Supporting Information of this article.
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