On the Occurrence of Zellia from the Maping Limestone of Chengkung, Central Yunnan

INTRODUCTIONThe specimens described in the present paper were collected in 1939 by the late Mr. T. Y. Hsu and Mr. C. S. Pien from the Maping limestone exposed E of Tuikoshan, Chengkung district, Central Yunnan. All specimens belong to Zellia, a subgenus of Pseudoschwagerina; three forms may be referred to known subspecies while two are new.     

Observational study of the seasonality of the submonthly and intraseasonal signal over the tropics

Summary Atmospheric variability in outgoing long-wave radiation (OLR) and tropospheric relative vorticity (VOR) over the South American region was studied from 1979 to 1996 using the complex Morlet wavelet function. The analyses focus on spatial variation in intraseasonal and submonthly scales. Scalograms were used to measure submonthly intraseasonal oscillations in convection, which were found to be predominant in the tropical regions. However, 7-day and 15-day oscillations were observed at tropical and extratropical latitudes in spring and winter, indicating that transient disturbances play a more prominent role. Regarding VOR, tropical energy intensities were highest in the spring and summer, whereas subtropical and extratropical energy intensities were highest in the autumn and winter. The dynamics of the 25-day and 45-day VOR oscillations indicates a possible correlation with Rossby waves over the eastern tropical Pacific Ocean, mainly during the summer. During winter, the 7-day and 15-day VOR oscillations are more frequent at higher latitudes and are enhanced along storm tracks. It was also observed that convection amplitudes in the regions of maximum intensity change appreciably from year to year and from season to season, showing that the behavior of the submonthly and intraseasonal oscillations is nonperiodic and correlates strongly with El Ni?o/Southern Oscillation years. These results confirm the efficiency of wavelet analysis for time-scale studies of atmospheric variability.     

Sedimentological analysis of two drill cores through the crater moat‐filling breccia,Flynn Creek impact structure,Tennessee

Sedimentological (line‐logging) analysis of two drill cores, FC77‐3 and FC67‐3, situated, respectively, in the northwestern and southeastern quadrants of the Flynn Creek impact structure's crater‐moat area reveals that the ~27 m thick crater moat‐filling breccia consists of three subequal parts. These parts, which were deposited during early modification stage of this marine‐target impact structure, are distinguished on the basis of vertical trends in sorting, grain size, and counts of clasts per meter in comparison with other well‐known marine‐target impact structures, namely Lockne, Tvären, and Chesapeake Bay. The lower part is interpreted to represent mainly slump deposits, and the middle part is interpreted to represent a stage intermediate between slump and marine resurge, that is, a traction flow driven by overriding suspension flow. The upper part (size graded, and relatively well sorted and fine grained) is interpreted to represent marine resurge flow only. The upper part is capped by a relatively thin and relatively fine‐grained calcarenite to calcisiltite deposit.     

Oxygen and hydrogen isotope fractionation in serpentine-water and talc-water systems from 250 to 450 °C, 50 MPa

Oxygen and hydrogen isotope fractionation factors in the talc-water and serpentine-water systems have been determined by laboratory experiment from 250 to 450 °C at 50 MPa using the partial exchange technique. Talc was synthesized from brucite + quartz, resulting in nearly 100% exchange during reaction at 350 and 450 °C. For serpentine, D-H exchange was much more rapid than ¹⁸O-¹⁶O exchange when natural chrysotile fibers were employed in the initial charge. In experiments with lizardite as the starting charge, recrystallization to chrysotile enhanced the rate of ¹⁸O-¹⁶O exchange with the coexisting aqueous phase. Oxygen isotope fractionation factors in both the talc-water and serpentine-water systems decrease with increasing temperature and can be described from 250 to 450 °C by the relationships: 1000 ln  = 11.70 × 10⁶/T² − 25.49 × 10³/T + 12.48 and 1000 ln  = 3.49 × 10⁶/T² − 9.48 where T is temperature in Kelvin. Over the same temperature interval at 50 MPa, talc-water D-H fractionation is only weakly dependent on temperature, similar to brucite and chlorite, and can be described by the equation: 1000 ln = 10.88 × 10⁶/T² − 41.52 × 10³/T + 5.61 where T is temperature in Kelvin. Our D-H serpentine-water fractionation factors calibrated by experiment decrease with temperature and form a consistent trend with fractionation factors derived from lower temperature field calibrations. By regression of these data, we have refined and extended the D-H fractionation curve from 25 to 450 °C, 50 MPa as follows: 1000 ln  = 3.436 × 10⁶/T² − 34.736 × 10³/T + 21.67 where T is temperature in Kelvin. These new data should improve the application of D-H and ¹⁸O-¹⁶O isotopes to constrain the temperature and origin of hydrothermal fluids responsible for serpentine formation in a variety of geologic settings.     

N and O isotope effects during nitrate assimilation by unicellular prokaryotic and eukaryotic plankton cultures

In order to provide biological systematics from which to interpret nitrogen (N) and oxygen (O) isotope ratios of nitrate (¹⁵N/¹⁴N, ¹⁸O/¹⁶O, respectively) in the environment, we previously investigated the isotopic fractionation of nitrate during its assimilation by mono-cultures of eukaryotic algae (Granger et al., 2004). In this study, we extended our analysis to investigate nitrate assimilation by strains of prokaryotic plankton. We measured the N and O isotope effects, ¹⁵ε and ¹⁸ε, during nitrate consumption by cultures of prokaryotic strains and by additional eukaryotic phytoplankton strains (where ε is the ratio of reaction rate constants of the light vs. heavy isotopologues, ^lightk and ^heavyk; ε = ^lightk/^heavyk − 1 × 1000, expressed in per mil). The observed ¹⁵ε ranged from 5‰ to 8‰ among eukaryotes, whereas it did not exceed 5‰ for three cyanobacterial strains, and was as low as 0.4‰ for a heterotrophic α-protoeobacterium. Eukaryotic phytoplankton fractionated the N and O isotopes of nitrate to the same extent (i.e., ¹⁸ε ∼ ¹⁵ε). The ¹⁸ε:¹⁵ε among the cyanobacteria was also ∼1, whereas the heterotrophic α-proteobacterial strain, which showed the lowest ¹⁵ε, between 0.4‰ and 1‰, had a distinct ¹⁸ε:¹⁵ε of ∼2, unlike any plankton strain observed previously. Equivalent N vs. O isotope discrimination is thought to occur during internal nitrate reduction by nitrate reductase, such that the cellular efflux of the fractionated nitrate into the medium drives the typically observed ¹⁸ε:¹⁵ε of ∼1. We hypothesize that the higher in the ¹⁸ε:¹⁵ε of the α-proteobacterium may result from isotope discrimination by nitrate transport, which is evident only at low amplitude of ε. These observations warrant investigating whether heterotrophic bacterial assimilation of nitrate decreases the community isotope effects at the surface ocean.     

The role of prior model calibration on predictions with ensemble Kalman filter

This paper, based on a real world case study (Limmat aquifer, Switzerland), compares inverse groundwater flow models calibrated with specified numbers of monitoring head locations. These models are updated in real time with the ensemble Kalman filter (EnKF) and the prediction improvement is assessed in relation to the amount of monitoring locations used for calibration and updating. The prediction errors of the models calibrated in transient state are smaller if the amount of monitoring locations used for the calibration is larger. For highly dynamic groundwater flow systems a transient calibration is recommended as a model calibrated in steady state can lead to worse results than a noncalibrated model with a well-chosen uniform conductivity. The model predictions can be improved further with the assimilation of new measurement data from on-line sensors with the EnKF. Within all the studied models the reduction of 1-day hydraulic head prediction error (in terms of mean absolute error [MAE]) with EnKF lies between 31% (assimilation of head data from 5 locations) and 72% (assimilation of head data from 85 locations). The largest prediction improvements are expected for models that were calibrated with only a limited amount of historical information. It is worthwhile to update the model even with few monitoring locations as it seems that the error reduction with EnKF decreases exponentially with the amount of monitoring locations used. These results prove the feasibility of data assimilation with EnKF also for a real world case and show that improved predictions of groundwater levels can be obtained.     

Modelling changes in the epidemic range of Southern Pine Beetle using temperature and objective moisture indicators

Summary This report details as statistical model that relates changes in areal coverage of the Southern Pine Beetle (Dendroctonus frontalis Zimm.) to a multivariate combination of temperature and moisture status indices. It is applicable to larger geographic areas than our previous work (Michaels 1984). Performance in a true test (predictive) mode detected the algebraic sign of major coverage changes in a highly significant fashion. The results are purely correlative, rather than causative.This report describes a test-proven tool that can be used by planners to determine whether coverage will change, based upon easily accessed climatic data. An example of its application is provided.

---

Zusammenfassung Diese Untersuchung führt ein statistisches Modell aus, welches das flächenmäßige Auftreten vonDendroctonus frontalis Zimm. mit einer Kombination von Temperaturund Feuchteverhältnisindikatoren in Verbindung bringt. Es kann für größere Gebiete verwendet werden als ein früher vorgestelltes (Michaels 1984). Die Anwendung zur Vorhersage zeigte in einem Test gute Übereinstimmung mit der tatsächlich aufgetretenen Richtung der Veränderung in der Verbreitung des Käfers. Die Ergebnisse zeigen Korrelationen, keine Kausalitäten auf.Es wird also ein Werkzeug für den Planer vorgestellt, mit dem die Verbreitungsänderung mit Hilfe leicht zugänglicher klimatologischer Daten bestimmt werden kann. Ein Anwendungsbeispiel wird näher ausgeführt.

---

---

With 5 Figures