Simulation of within field variability of corn yield with Ceres-Maize model

The CERES-Maize model was used to estimate the spatial variability in corn (Zea mays L.) yield for 1995 and 1996 using data measured on soil profiles located on a 30.5 m grid within a 3.9 ha field in Michigan. The model was calibrated for one grid profile for the 1995 and then used to simulate corn yield for all grid points for the 2 yrs. For the calibration for 1995, the model predicted corn yield within 2%. For 1995, the model predicted yield variability very well (r(2) = 0.85), producing similar yield maps with differences generally within +/- 300 kg ha(-1). For 1996, the model predicted low grain yields (1167 kg ha(-1)) compared with measured (8928 kg ha(-1)) because the model does not account for horizontal water movement within the landscape or water contributions from a water table. Under nonlimiting water conditions, the model performed well (average of 8717 vs. 8948 kg ha(-1)) but under-estimated the measured yield variability.

Geoffroy's side-necked turtle [Phrynops geoffroanus (Schweigger, 1812), Testudines: Chelidae] as a model for evolutionary ecotoxicology: relationship between environmental contamination, conditions and genetic variability

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Height variability from the MIROC - IPCC model for the 20th century compared to that of the TOPEX/POSEIDON altimeter

Planetary waves are key to large-scale dynamical adjustment in the global ocean as they transfer energy from the east to the west side of oceanic basins; they connect the forcing in the ocean interior with the variability at its boundaries: and they change the local heat content, thus coupling oceanic, atmospheric, and biological processes. Planetary waves, mostly of the first baroclinic mode, are observed as distinctive patterns in global time series of sea surface height anomaly (SSHA) and heat storage. The goal of this study is to compare and validate large-scale SSHA signals from coupled ocean-atmosphere general circulation Model for Interdisciplinary Research on Climate (MIROC) with TOPEX/POSEIDON satellite altimeter observations. The last decade of the models` time series is selected for comparison with the altimeter data. The wave patterns are separated from the meso- and large-scale SSHA signals by digital filters calibrated to select the same spectral bands in both model and altimeter data. The band-wise comparison allows for an assessment of the model skill to simulate the dynamical components of the observed wave field. Comparisons regarding both the seasonal cycle and the Rossby wave Held differ significantly among basins. When carried within the same basin, differences can occur between equal latitudes in opposite hemispheres. Furthermore, at some latitudes the MIROC reproduces biannual, annual and semiannual planetary waves with phase speeds and average amplitudes similar to those observed by the altimeter, but with significant differences in phase. (C) 2008 Elsevier Ltd. All rights reserved.

Bayesian model accounting for within-class biological variability in Serial Analysis of Gene Expression (SAGE)

Abstract Background An important challenge for transcript counting methods such as Serial Analysis of Gene Expression (SAGE), "Digital Northern" or Massively Parallel Signature Sequencing (MPSS), is to carry out statistical analyses that account for the within-class variability, i.e., variability due to the intrinsic biological differences among sampled individuals of the same class, and not only variability due to technical sampling error. Results We introduce a Bayesian model that accounts for the within-class variability by means of mixture distribution. We show that the previously available approaches of aggregation in pools ("pseudo-libraries") and the Beta-Binomial model, are particular cases of the mixture model. We illustrate our method with a brain tumor vs. normal comparison using SAGE data from public databases. We show examples of tags regarded as differentially expressed with high significance if the within-class variability is ignored, but clearly not so significant if one accounts for it. Conclusion Using available information about biological replicates, one can transform a list of candidate transcripts showing differential expression to a more reliable one. Our method is freely available, under GPL/GNU copyleft, through a user friendly web-based on-line tool or as R language scripts at supplemental web-site.

Loudness scattering due to vibro-acoustic model variability

The use of numerical simulation in the design and evaluation of products performance is ever increasing. To a greater extent, such estimates are needed in a early design stage, when physical prototypes are not available. When dealing with vibro-acoustic models, known to be computationally expensive, a question remains, which is related to the accuracy of such models in view of the well-know variability inherent to the mass manufacturing production techniques. In addition, both academia and industry have recently realized the importance of actually listening to a products sound, either by measurements or by virtual sound synthesis, in order to assess its performance. In this work, the scatter of significant parameter variations on a simplified vehicle vibro-acoustic model is calculated on loudness metrics using Monte Carlo analysis. The mapping from the system parameters to sound quality metric is performed by a fully-coupled vibro-acoustic finite element model. Different loudness metrics are used, including overall sound pressure level expressed in dB and Specific Loudness in Sones. Sound quality equivalent sources are used to excite this model and the sound pressure level at the driver's head position is acquired to be evaluated according to sound quality metrics. No significant variation has been perceived when evaluating the system using regular sound pressure level expressed in in dB and dB(A). This happens because of the third-octave filters that averages the results under some frequency bands. On the other hand, Zwicker Loudness presents important variations, arguably, due to the masking effects.

Enhanced Atlantic subpolar gyre variability through baroclinic threshold in a coarse resolution model

Direct observations, satellite measurements and paleo records reveal strong variability in the Atlantic subpolar gyre on various time scales. Here we show that variations of comparable amplitude can only be simulated in a coupled climate model in the proximity of a dynamical threshold. The threshold and the associated dynamic response is due to a positive feedback involving increased salt transport in the subpolar gyre and enhanced deep convection in its centre. A series of sensitivity experiments is performed with a coarse resolution ocean general circulation model coupled to a statistical-dynamical atmosphere model which in itself does not produce atmospheric variability. To simulate the impact of atmospheric variability, the model system is perturbed with freshwater forcing of varying, but small amplitude and multi-decadal to centennial periodicities and observational variations in wind stress. While both freshwater and wind-stress-forcing have a small direct effect on the strength of the subpolar gyre, the magnitude of the gyre's response is strongly increased in the vicinity of the threshold. Our results indicate that baroclinic self-amplification in the North Atlantic ocean can play an important role in presently observed SPG variability and thereby North Atlantic climate variability on multi-decadal scales.

Mechanisms of intrinsic beating variability in cardiac cell cultures and model pacemaker networks

Heart rate variability (HRV) exhibits fluctuations characterized by a power law behavior of its power spectrum. The interpretation of this nonlinear HRV behavior, resulting from interactions between extracardiac regulatory mechanisms, could be clinically useful. However, the involvement of intrinsic variations of pacemaker rate in HRV has scarcely been investigated. We examined beating variability in spontaneously active incubating cultures of neonatal rat ventricular myocytes using microelectrode arrays. In networks of mathematical model pacemaker cells, we evaluated the variability induced by the stochastic gating of transmembrane currents and of calcium release channels and by the dynamic turnover of ion channels. In the cultures, spontaneous activity originated from a mobile focus. Both the beat-to-beat movement of the focus and beat rate variability exhibited a power law behavior. In the model networks, stochastic fluctuations in transmembrane currents and stochastic gating of calcium release channels did not reproduce the spatiotemporal patterns observed in vitro. In contrast, long-term correlations produced by the turnover of ion channels induced variability patterns with a power law behavior similar to those observed experimentally. Therefore, phenomena leading to long-term correlated variations in pacemaker cellular function may, in conjunction with extracardiac regulatory mechanisms, contribute to the nonlinear characteristics of HRV.

Decadal Variability in the Northeast Pacific in a Physical-Ecosystem Model: Role of Mixed Layer Depth and Trophic Interactions

A basin-wide interdecadal change in both the physical state and the ecology of the North Pacific occurred near the end of 1976. Here we use a physical-ecosystem model to examine whether changes in the physical environment associated with the 1976-1977 transition influenced the lower trophic levels of the food web and if so by what means. The physical component is an ocean general circulation model, while the biological component contains 10 compartments: two phytoplankton, two zooplankton, two detritus pools, nitrate, ammonium, silicate, and carbon dioxide. The model is forced with observed atmospheric fields during 1960-1999. During spring, there is a similar to 40% reduction in plankton biomass in all four plankton groups during 1977-1988 relative to 1970-1976 in the central Gulf of Alaska (GOA). The epoch difference in plankton appears to be controlled by the mixed layer depth. Enhanced Ekman pumping after 1976 caused the halocline to shoal, and thus the mixed layer depth, which extends to the top of the halocline in late winter, did not penetrate as deep in the central GOA. As a result, more phytoplankton remained in the euphotic zone, and phytoplankton biomass began to increase earlier in the year after the 1976 transition. Zooplankton biomass also increased, but then grazing pressure led to a strong decrease in phytoplankton by April followed by a drop in zooplankton by May: Essentially, the mean seasonal cycle of plankton biomass was shifted earlier in the year. As the seasonal cycle progressed, the difference in plankton concentrations between epochs reversed sign again, leading to slightly greater zooplankton biomass during summer in the later epoch.

A multi-model comparison of Atlantic multidecadal variability

A multi-model analysis of Atlantic multidecadal variability is performed with the following aims: to investigate the similarities to observations; to assess the strength and relative importance of the different elements of the mechanism proposed by Delworth et al. (J Clim 6:1993–2011, 1993) (hereafter D93) among coupled general circulation models (CGCMs); and to relate model differences to mean systematic error. The analysis is performed with long control simulations from ten CGCMs, with lengths ranging between 500 and 3600 years. In most models the variations of sea surface temperature (SST) averaged over North Atlantic show considerable power on multidecadal time scales, but with different periodicity. The SST variations are largest in the mid-latitude region, consistent with the short instrumental record. Despite large differences in model configurations, we find quite some consistency among the models in terms of processes. In eight of the ten models the mid-latitude SST variations are significantly correlated with fluctuations in the Atlantic meridional overturning circulation (AMOC), suggesting a link to northward heat transport changes. Consistent with this link, the three models with the weakest AMOC have the largest cold SST bias in the North Atlantic. There is no linear relationship on decadal timescales between AMOC and North Atlantic Oscillation in the models. Analysis of the key elements of the D93 mechanisms revealed the following: Most models present strong evidence that high-latitude winter mixing precede AMOC changes. However, the regions of wintertime convection differ among models. In most models salinity-induced density anomalies in the convective region tend to lead AMOC, while temperature-induced density anomalies lead AMOC only in one model. However, analysis shows that salinity may play an overly important role in most models, because of cold temperature biases in their relevant convective regions. In most models subpolar gyre variations tend to lead AMOC changes, and this relation is strong in more than half of the models.