Comparing and evaluating process-based ecosystem model predictions of carbon and water fluxes in major European forest biomes

Process‐based models can be classified into: (a) terrestrial biogeochemical models (TBMs), which simulate fluxes of carbon, water and nitrogen coupled within terrestrial ecosystems, and (b) dynamic global vegetation models (DGVMs), which further couple these processes interactively with changes in slow ecosystem processes depending on resource competition, establishment, growth and mortality of different vegetation types. In this study, four models – RHESSys, GOTILWA+, LPJ‐GUESS and ORCHIDEE – representing both modelling approaches were compared and evaluated against benchmarks provided by eddy‐covariance measurements of carbon and water fluxes at 15 forest sites within the EUROFLUX project. Overall, model‐measurement agreement varied greatly among sites. Both modelling approaches have somewhat different strengths, but there was no model among those tested that universally performed well on the two variables evaluated. Small biases and errors suggest that ORCHIDEE and GOTILWA+ performed better in simulating carbon fluxes while LPJ‐GUESS and RHESSys did a better job in simulating water fluxes. In general, the models can be considered as useful tools for studies of climate change impacts on carbon and water cycling in forests. However, the various sources of variation among models simulations and between models simulations and observed data described in this study place some constraints on the results and to some extent reduce their reliability. For example, at most sites in the Mediterranean region all models generally performed poorly most likely because of problems in the representation of water stress effects on both carbon uptake by photosynthesis and carbon release by heterotrophic respiration (R_h). The use of flux data as a means of assessing key processes in models of this type is an important approach to improving model performance. Our results show that the models have value but that further model development is necessary with regard to the representation of the some of the key ecosystem processes.     

Modeling Response of N Addition on C and N Allocation in Scandinavian Norway Spruce Stands

Because nitrogen is considered to be the major growth-limiting element in boreal forests, the increasing nitrogen availability from deposition should lead to increasing growth. We have tested this assumption by simulating, with a simple model, carbon and nitrogen development in seven long-term fertilization experiments in three Nordic countries. The only differences between sites in the model are climate, the ambient nitrogen deposition, nitrogen fertilization regimes, and the initial conditions at the start of the experiment. The model simulates the observed stand development well as long as nitrogen remains the limiting factor. The simulated retention of deposited nitrogen is in general low (less than 50%), whereas retention of fertilizer nitrogen is higher. This seems to imply that the higher production in the fertilized stands will not be maintained once the fertilization is stopped. The model results also indicate that the major effect of climate on site productivity is through soil processes, not tree physiology.     

Hematopoietic chimerism monitoring based on STRs: quantitative platform performance on sequential samples.

Hematopoietic stem cell transplantation (HSCT) creates a donor-recipient cellular chimerism in the patient, which is quantitatively assayed from peripheral blood based on STR-DNA. Since chimerism values often vary across a patient's samples, it is important to determine to what extent this variability reflects technical aspects of platform performance. This issue is systematically assessed in the current study for the first time. Using the SGM Plus multiplex PCR kit and ABI platform, the longitudinal performance of STR markers was quantitatively evaluated in two chimeric models with true values, and in patient samples (n >500 marker loci). Computation of percent chimerism for each marker, and mean (sample) percent chimerism, standard deviation, and coefficient of variance was performed by our ChimerTrack utility. In chimeric models with known values, individual markers exhibited an accuracy (observed/true) of 88-98%; replication precision was 92-100% true, with a mean error of 2%. Fragment size calling was greater than 99% accurate and precise. Patient results were comparable for markers, relaive to sample means. One source of technical variability in chimerism estimation was allelic differential amplification efficiency. The latter was influenced by signal amplitude, dye label, marker size, and allelic size interval. It can be concluded that long-term chimeric tracking is routinely feasible using this platform in conjunction with ChimerTrack software. Importantly, mean percent chimerism, for any sample, should closely approximate the true chimeric status, with a technical accuracy of 98%. Guidelines are presented for selecting an optimized marker profile.     

Spatial heterogeneity and population risk analysis of cotton bollworm, Helicoverpa armigera, in China

In this study, semivariance was used to quantitatively measure the spatial heterogeneity for the egg population of cotton bollworm during a growing season. The typical characteristic parameters of theoretical semivariance models against lag distances were applied to measure components of spatial heterogeneity： trend, range, spatial dependence, and the strength of spatial dependence. Then, kriging interpolation was used to evaluate the population risk of cotton bollworm exceeding economic thresholds. From early June through early September, the population densities were sampled 10 times in the study field. Results showed that the spatial patterns were related to population density. For its low-density population, the spatially heterogeneous trends were usually of spherical shapes; but for highdensity ones, the trends shifted to Gaussian shapes. The spatial dependence appeared at varied distances ranging from 52 meters to 936 meters, and the spatial dependence was in the range of 0.39-288.60, which changed with population densities. While having high heterogeneity, the strength of spatial dependence became much stronger. Results of population risk analysis showed that there was a high risk during its early stages, especially in mid-June. In August, population risk was so low that it did not need to be controlled.     

Inactivation and sensitization of tumor cells after transfection with gene Bax

Experiments on the transfection of cultured SKOV3 tumor cells of human ovarian adenocarcinoma and HeLa cells of human cervical carcinoma with gene Bax have demonstrated that SKOV3 cells are highly sensitive to the protein product of this gene, whereas the sensitivity of HeLa cells is substantially lower. HeLa cells obtained as a result of Bax transfection and subsequent selection are characterized by an extremely high Bax protein content and a hypersensitivity to doxorubicin. All Bax-transfected SKOV3 cells with an increased Bax content have died. In the SKOV3 cell line, a Bax exon 3 mutation has been found that corresponds to genotype G7/G9, whereas the native type of the Bax gene corresponds to genotype G8/G8. The results suggest that the G7/G9 mutation in Bax exon 3 deprives the Bax protein of proapoptotic activity.Translated from Molekulyarnaya Biologiya, Vol. 39, No. 1, 2005, pp. 40–47.Original Russian Text Copyright © 2005 by Rodina, Sladkova, Obuchova, Vezirkhanova, Moskaleva, Prusakova, Beletskii, Belushkina, Strelnikov, Ivanov, S. Severin, E. Severin.