Search

The coupling of an electron gas confined by a harmonic potential and submitted to a strong magnetic field tilted in relation to the confining direction creates an excitation called here magneto-polariton. This work describes the origin of this excitation and calculates the energy eigenvalues for different tilted angles. It presents the reasons leading to the crossings and repulsions of the energy bands, the degeneracy of the states, the way the Fermi levels change with the magnetic field, the influence of an external electric field, and how the Hall resistance plateaus change with the change in the tilted angle. [ABSTRACT FROM AUTHOR]

Phytoplankton photosynthesis links global ocean biology and climate-driven fluctuations in the physical environment. These interactions are largely expressed through changes in phytoplankton physiology, but physiological status has proven extremely challenging to characterize globally. Phytoplankton fluorescence does provide a rich source of physiological information long exploited in laboratory and field studies, and is now observed from space. Here we evaluate the physiological underpinnings of global variations in satellite-based phytoplankton chlorophyll fluorescence. The three dominant factors influencing fluorescence distributions are chlorophyll concentration, pigment packaging effects on light absorption, and light-dependent energy-quenching processes. After accounting for these three factors, resultant global distributions of quenching-corrected fluorescence quantum yields reveal a striking consistency with anticipated patterns of iron availability. High fluorescence quantum yields are typically found in low iron waters, while low quantum yields dominate regions where other environmental factors are most limiting to phytoplankton growth. Specific properties of photosynthetic membranes are discussed that provide a mechanistic view linking iron stress to satellite-detected fluorescence. Our results present satellite-based fluorescence as a valuable tool for evaluating nutrient stress predictions in ocean ecosystem models and give the first synoptic observational evidence that iron plays an important role in seasonal phytoplankton dynamics of the Indian Ocean. Satellite fluorescence may also provide a path for monitoring climate-phytoplankton physiology interactions and improving descriptions of phytoplankton light use efficiencies in ocean productivity models.

We quantify the mechanisms governing interannual variability in the global, upper-ocean inorganic carbon system using a hindcast simulation (1979-2004) of an ecosystem-biogeochemistry model forced with time-evolving atmospheric physics and dust deposition. We analyze the variability of three key, interrelated metrics-air-sea CO2 flux, surface-water carbon dioxide partial pressure pCO2, and upper-ocean dissolved inorganic carbon (DIC) inventory-presenting for each metric global spatial maps of the root mean square (rms) of anomalies from a model monthly climatology. The contribution of specific driving factors is diagnosed using Taylor expansions and linear regression analysis. The major regions of variability occur in the Southern Ocean, tropical Indo-Pacific, and Northern Hemisphere temperate and subpolar latitudes. Ocean circulation is the dominant factor driving variability over most of the ocean, modulating surface dissolved inorganic carbon that in turn alters surface-water pCO2 and air-sea CO2 flux variability (global integrated anomaly rms of 0.34 Pg C yr-1). Biological export and thermal solubility effects partially damp circulation-driven pCO2 variability in the tropics, while in the subtropics, thermal solubility contributes positively to surface-water pCO2 and air-sea CO2 flux variability. Gas transfer and net freshwater inputs induce variability in the air-sea CO2 flux in some specific regions. A component of air-sea CO2 flux variability (global integrated anomaly rms of 0.14 Pg C yr-1) arises from variations in biological export production induced by variations in atmospheric iron deposition downwind of dust source regions. Beginning in the mid-1990s, reduced global dust deposition generates increased air-sea CO2 outgassing in the Southern Ocean, consistent with trends derived from atmospheric CO2 inversions. © 2008 Elsevier Ltd.

Atmospheric aerosol deposition is an important source of nutrients and trace metals to the open ocean that can enhance ocean productivity and carbon sequestration and thus influence atmospheric carbon dioxide concentrations and climate. Using aerosol samples from different back trajectories in incubation experiments with natural communities, we demonstrate that the response of phytoplankton growth to aerosol additions depends on specific components in aerosols and differs across phytoplankton species. Aerosol additions enhanced growth by releasing nitrogen and phosphorus, but not all aerosols stimulated growth. Toxic effects were observed with some aerosols, where the toxicity affected picoeukaryotes and Synechococcus but notProchlorococcus. We suggest that the toxicity could be due to high copper concentrations in these aerosols and support this by laboratory copper toxicity tests preformed with Synechococcus cultures. However, it is possible that other elements present in the aerosols or unknown synergistic effects between these elements could have also contributed to the toxic effect. Anthropogenic emissions are increasing atmospheric copper deposition sharply, and based on coupled atmosphere–ocean calculations, we show that this deposition can potentially alter patterns of marine primary production and community structure in high aerosol, low chlorophyll areas, particularly in the Bay of Bengal and downwind of South and East Asia.

Depth-integrated primary productivity (PP) estimates obtained from satellite ocean color-based models (SatPPMs) and those generated from biogeochemical ocean general circulation models (BOGCMs) represent a key resource for biogeochemical and ecological studies at global as well as regional scales. Calibration and validation of these PP models are not straightforward, however, and comparative studies show large differences between model estimates. The goal of this paper is to compare PP estimates obtained from 30 different models (21 SatPPMs and 9 BOGCMs) to a tropical Pacific PP database consisting of ∼ 1000 14C measurements spanning more than a decade (1983-1996). Primary findings include: skill varied significantly between models, but performance was not a function of model complexity or type (i.e. SatPPM vs. BOGCM); nearly all models underestimated the observed variance of PP, specifically yielding too few low PP (< 0.2 g C m- 2 d- 1) values; more than half of the total root-mean-squared model-data differences associated with the satellite-based PP models might be accounted for by uncertainties in the input variables and/or the PP data; and the tropical Pacific database captures a broad scale shift from low biomass-normalized productivity in the 1980s to higher biomass-normalized productivity in the 1990s, which was not successfully captured by any of the models. This latter result suggests that interdecadal and global changes will be a significant challenge for both SatPPMs and BOGCMs. Finally, average root-mean-squared differences between in situ PP data on the equator at 140°W and PP estimates from the satellite-based productivity models were 58% lower than analogous values computed in a previous PP model comparison 6 years ago. The success of these types of comparison exercises is illustrated by the continual modification and improvement of the participating models and the resulting increase in model skill. © 2008 Elsevier B.V.

We present a generalized framework for assessing the skill of global upper ocean ecosystem-biogeochemical models against in-situ field data and satellite observations. We illustrate the approach utilizing a multi-decade (1979-2004) hindcast experiment conducted with the Community Climate System Model (CCSM-3) ocean carbon model. The CCSM-3 ocean carbon model incorporates a multi-nutrient, multi-phytoplankton functional group ecosystem module coupled with a carbon, oxygen, nitrogen, phosphorus, silicon, and iron biogeochemistry module embedded in a global, three-dimensional ocean general circulation model. The model is forced with physical climate forcing from atmospheric reanalysis and satellite data products and time-varying atmospheric dust deposition. Data-based skill metrics are used to evaluate the simulated time-mean spatial patterns, seasonal cycle amplitude and phase, and subannual to interannual variability. Evaluation data include: sea surface temperature and mixed layer depth; satellite-derived surface ocean chlorophyll, primary productivity, phytoplankton growth rate and carbon biomass; large-scale climatologies of surface nutrients, pCO2, and air-sea CO2 and O2 flux; and time-series data from the Joint Global Ocean Flux Study (JGOFS). Where the data is sufficient, we construct quantitative skill metrics using: model-data residuals, time-space correlation, root mean square error, and Taylor diagrams. © 2008 Elsevier B.V. All rights reserved.

The feeding of bees is an important factor for their survival, and currently, the use of transgenics is common among producers, since the use of these has reduced production costs, however, there is a great debate as to whether transgenics can harm pollinators. that are in farming regions. Thus, the objective was to evaluate the longevity of Apis mellifera bees using different compositions of transgenic and conventional soy and corn diets, foods that can be substitutes for pollen as a protein source for the hive. For that, the theory of Survival Analysis was used, where the data were constituted by interval censorship, because the time of death is not exactly known. The survival function was estimated using the Weibull regression model with the presence of two covariables: whether the diet is transgenic or not, and the protein content. The adequacy of the model was verified by the graphs of the linearizations using a script developed for the Survival package of the R software, in addition to carrying out the likelihood ratio test at 1% probability, concluding that the presence of the two covariables in the model is significant. In this way, the survival curves of the bees and the estimated risk were constructed, concluding that the GM foods did not have a negative effect on the survival of the bees. [ABSTRACT FROM AUTHOR]

Climate variability drives significant changes in the physical state of the North Pacific, and there may be important impacts of this variability on the upper ocean carbon balance across the basin. We address this issue by considering the response of seven biogeochemical ocean models to climate variability in the North Pacific. The models' upper ocean pCO2 and air-sea CO2 flux respond similarly to climate variability on seasonal to decadal timescales. Modeled seasonal cycles of pCO2 and its temperature- and non-temperature-driven components at three contrasting oceanographic sites capture the basic features found in observations (Takahashi et al., 2002, 2006; Keeling et al., 2004; Brix et al., 2004). However, particularly in the Western Subarctic Gyre, the models have difficulty representing the temporal structure of the total pCO2 seasonal cycle because it results from the difference of these two large and opposing components. In all but one model, the air-sea CO2 flux interannual variability (1σ) in the North Pacific is smaller (ranges across models from 0.03 to 0.11 PgC/yr) than in the Tropical Pacific (ranges across models from 0.08 to 0.19 PgC/yr), and the time series of the first or second EOF of the air-sea CO2 flux has a significant correlation with the Pacific Decadal Oscillation (PDO). Though air-sea CO2 flux anomalies are correlated with the PDO, their magnitudes are small (up to ±0.025 PgC/yr (1σ)). Flux anomalies are damped because anomalies in the key drivers of pCO2 (temperature, dissolved inorganic carbon (DIC), and alkalinity) are all of similar magnitude and have strongly opposing effects that damp total pCO2 anomalies.

Astrometric studies and orbital modelling of planetary moons have contributed significantly to advancing our understanding of their orbital dynamics. These studies require precise positions measured over extended periods. In this paper, we present the results of the 2021 Brazilian Jovian mutual phenomena campaign. The data correspond to eight events between Galilean satellites, in addition to a rare eclipse of Thebe, an inner satellite, totalling nine events. A geometric model along with the DE440/JUP365 ephemerides was used to reproduce the events and simulate the light curves. A Monte Carlo method and chi-squared statistics were used to fit the simulated light curves to the observations. The reflectance model adopted for our simulations was the complete version of the Oren–Nayer model. The average uncertainty of the relative positions of the Galilean satellites was 5 mas (15 km) and for the inner Thebe satellite 32 mas (96 km). The seven mutual events (nine independent observations) here analysed represent an addition of 17 per cent events (10 per cent light curves) with respect to the 2021 international mutual phenomena campaign. Furthermore, our result of Thebe eclipse is only the second measurement published to date. Our results contribute to the ephemeris data base, being fundamental to improving satellite orbits and thus minimizing their uncertainties. [ABSTRACT FROM AUTHOR]

Let p be a prime and E an extra-special p-group of exponent p and order p 2 n + 1 . Suppose that E acts by automorphisms on a finite p ′ -group G. We prove that if γ n (C G (a)) is nilpotent for any a ∈ E # , then γ n (G) is nilpotent. If, for some integer d such that 2 d ≤ n , the dth derived group of C G (a) is nilpotent for any a ∈ E # , then the dth derived group G (d) is nilpotent. We also prove similar results for Lie algebras. [ABSTRACT FROM AUTHOR]