Magnitude of climate variability during middle Pliocene warmth: a palaeoclimate modelling study

The nature and magnitude of climatic variability during the period of middle Pliocene warmth (ca 3.29–2.97 Ma) is poorly understood. We present a suite of palaeoclimate modelling experiments incorporating an advanced atmospheric general circulation model (GCM), coupled to a Q-flux ocean model for 3.29, 3.12 and 2.97 Ma BP. Astronomical solutions for the periods in question were derived from the Berger and Loutre BL2 astronomical solution. Boundary conditions, excluding sea surface temperatures (SSTs) which were predicted by the slab-ocean model, were provided from the USGS PRISM2 2°×2° digital data set. The model results indicate that little annual variation (0.5°C) in SSTs, relative to a ‘control’ experiment, occurred during the middle Pliocene in response to the altered orbital configurations. Annual surface air temperatures also displayed little variation. Seasonally, surface air temperatures displayed a trend of cooler temperatures during December, January and February, and warmer temperatures during June, July and August. This pattern is consistent with altered seasonality resulting from the prescribed orbital configurations. Precipitation changes follow the seasonal trend observed for surface air temperature. Compared to present-day, surface wind strength and wind stress over the North Atlantic, North Pacific and Southern Ocean remained greater in each of the Pliocene experiments. This suggests that wind-driven gyral circulation may have been consistently greater during the middle Pliocene. The trend of climatic variability predicted by the GCM for the middle Pliocene accords with geological data. However, it is unclear if the model correctly simulates the magnitude of the variation. This uncertainty is derived from, (a) the relative insensitivity of the GCM to perturbation in the imposed boundary conditions, (b) a lack of detailed time series data concerning changes to terrestrial ice cover and greenhouse gas concentrations for the middle Pliocene and (c) difficulties in representing the effects of ‘climatic history’ in snap-shot GCM experiments.

Biodiversity of Collembola in urban soils and the use of Folsomia candida to assess soil 'quality'

The effects of metal contamination on natural populations of Collembola in soils from five sites in the Wolverhampton area ( West Midlands, England) were examined. Analysis revealed that metal concentrations were elevated above background levels at all sites. One location in particular (Ladymoor, a former smelting site) was highly contaminated with Cd, Cu, Pb and Zn at more than 20 times background levels. Biodiversity indices ( Shannon - Weiner, Simpson index, Margalef index, alpha index, species richness, Shaneven ( evenness) and Berger - Parker dominance) were calculated. Of these indices, estimates of species richness and evenness were most effective at highlighting the differences between the Collembola communities. Indeed, the highest number of species were found at the most contaminated site, although the Collembola population also had a comparatively low evenness value, with just two species dominating. The number of individuals per species were allocated into geometric classes and plotted against the cumulative number of species as a percentage. At Ladymoor, there were more geometric classes, and the slope of the line was shallower than at the other four sites. This characteristic is a feature of polluted sites, where a few species are dominant and most species are rare. The Ladymoor soil also had a dominance of Isotomurus palustris, and was the only site in which Ceratophysella denticulata was found. Previous studies have shown that these two species are often found in sites subject to high metal contamination. Survival and reproduction of the "standard'' test springtail, Folsomia candida (Willem), were determined in a 4 week exposure test to soils from all five sites. Mortality was significantly increased in adults and reproduction significantly lower in the Ladymoor soil in comparison to the other four sites. This study has shown that severe metal contamination can be related to the population structure of Collembola in the field, and performance of F. candida ( in soils from such sites) in the laboratory.

A jackknife variance estimator for unequal probability sampling

The jackknife method is often used for variance estimation in sample surveys but has only been developed for a limited class of sampling designs.We propose a jackknife variance estimator which is defined for any without-replacement unequal probability sampling design. We demonstrate design consistency of this estimator for a broad class of point estimators. A Monte Carlo study shows how the proposed estimator may improve on existing estimators.

Variance estimation with highly stratified sampling designs with unequal probabilities

It is common practice to design a survey with a large number of strata. However, in this case the usual techniques for variance estimation can be inaccurate. This paper proposes a variance estimator for estimators of totals. The method proposed can be implemented with standard statistical packages without any specific programming, as it involves simple techniques of estimation, such as regression fitting.

Variance estimation for systematic sampling from deliberately ordered populations

The systematic sampling (SYS) design (Madow and Madow, 1944) is widely used by statistical offices due to its simplicity and efficiency (e.g., Iachan, 1982). But it suffers from a serious defect, namely, that it is impossible to unbiasedly estimate the sampling variance (Iachan, 1982) and usual variance estimators (Yates and Grundy, 1953) are inadequate and can overestimate the variance significantly (Särndal et al., 1992). We propose a novel variance estimator which is less biased and that can be implemented with any given population order. We will justify this estimator theoretically and with a Monte Carlo simulation study.

Variance estimation with Chao's sampling scheme

We show that the Hájek (Ann. Math Statist. (1964) 1491) variance estimator can be used to estimate the variance of the Horvitz–Thompson estimator when the Chao sampling scheme (Chao, Biometrika 69 (1982) 653) is implemented. This estimator is simple and can be implemented with any statistical packages. We consider a numerical and an analytic method to show that this estimator can be used. A series of simulations supports our findings.

Adjusted jackknife for imputation under unequal probability sampling without replacement

Imputation is commonly used to compensate for item non-response in sample surveys. If we treat the imputed values as if they are true values, and then compute the variance estimates by using standard methods, such as the jackknife, we can seriously underestimate the true variances. We propose a modified jackknife variance estimator which is defined for any without-replacement unequal probability sampling design in the presence of imputation and non-negligible sampling fraction. Mean, ratio and random-imputation methods will be considered. The practical advantage of the method proposed is its breadth of applicability.

Biodiversity of Collembola in urban soils and the use of Folsomia candida to assess soil 'quality'

The effects of metal contamination on natural populations of Collembola in soils from five sites in the Wolverhampton area ( West Midlands, England) were examined. Analysis revealed that metal concentrations were elevated above background levels at all sites. One location in particular (Ladymoor, a former smelting site) was highly contaminated with Cd, Cu, Pb and Zn at more than 20 times background levels. Biodiversity indices ( Shannon - Weiner, Simpson index, Margalef index, alpha index, species richness, Shaneven ( evenness) and Berger - Parker dominance) were calculated. Of these indices, estimates of species richness and evenness were most effective at highlighting the differences between the Collembola communities. Indeed, the highest number of species were found at the most contaminated site, although the Collembola population also had a comparatively low evenness value, with just two species dominating. The number of individuals per species were allocated into geometric classes and plotted against the cumulative number of species as a percentage. At Ladymoor, there were more geometric classes, and the slope of the line was shallower than at the other four sites. This characteristic is a feature of polluted sites, where a few species are dominant and most species are rare. The Ladymoor soil also had a dominance of Isotomurus palustris, and was the only site in which Ceratophysella denticulata was found. Previous studies have shown that these two species are often found in sites subject to high metal contamination. Survival and reproduction of the "standard'' test springtail, Folsomia candida (Willem), were determined in a 4 week exposure test to soils from all five sites. Mortality was significantly increased in adults and reproduction significantly lower in the Ladymoor soil in comparison to the other four sites. This study has shown that severe metal contamination can be related to the population structure of Collembola in the field, and performance of F. candida ( in soils from such sites) in the laboratory.

A comparative study of multilayered and single layered neural network based predictive controllers

The authors compare the performance of two types of controllers one based on the multilayered network and the other based on the single layered CMAC network (cerebellar model articulator controller). The neurons (information processing units) in the multi-layered network use Gaussian activation functions. The control scheme which is considered is a predictive control algorithm, along the lines used by Willis et al. (1991), Kambhampati and Warwick (1991). The process selected as a test bed is a continuous stirred tank reactor. The reaction taking place is an irreversible exothermic reaction in a constant volume reactor cooled by a single coolant stream. This reactor is a simplified version of the first tank in the two tank system given by Henson and Seborg (1989).

Colonization-induced host-gut microbial metabolic interaction

The gut microbiota enhances the host's metabolic capacity for processing nutrients and drugs and modulate the activities of multiple pathways in a variety of organ systems. We have probed the systemic metabolic adaptation to gut colonization for 20 days following exposure of axenic mice (n = 35) to a typical environmental microbial background using high-resolution (1)H nuclear magnetic resonance (NMR) spectroscopy to analyze urine, plasma, liver, kidney, and colon (5 time points) metabolic profiles. Acquisition of the gut microbiota was associated with rapid increase in body weight (4%) over the first 5 days of colonization with parallel changes in multiple pathways in all compartments analyzed. The colonization process stimulated glycogenesis in the liver prior to triggering increases in hepatic triglyceride synthesis. These changes were associated with modifications of hepatic Cyp8b1 expression and the subsequent alteration of bile acid metabolites, including taurocholate and tauromuricholate, which are essential regulators of lipid absorption. Expression and activity of major drug-metabolizing enzymes (Cyp3a11 and Cyp2c29) were also significantly stimulated. Remarkably, statistical modeling of the interactions between hepatic metabolic profiles and microbial composition analyzed by 16S rRNA gene pyrosequencing revealed strong associations of the Coriobacteriaceae family with both the hepatic triglyceride, glucose, and glycogen levels and the metabolism of xenobiotics. These data demonstrate the importance of microbial activity in metabolic phenotype development, indicating that microbiota manipulation is a useful tool for beneficially modulating xenobiotic metabolism and pharmacokinetics in personalized health care. IMPORTANCE: Gut bacteria have been associated with various essential biological functions in humans such as energy harvest and regulation of blood pressure. Furthermore, gut microbial colonization occurs after birth in parallel with other critical processes such as immune and cognitive development. Thus, it is essential to understand the bidirectional interaction between the host metabolism and its symbionts. Here, we describe the first evidence of an in vivo association between a family of bacteria and hepatic lipid metabolism. These results provide new insights into the fundamental mechanisms that regulate host-gut microbiota interactions and are thus of wide interest to microbiological, nutrition, metabolic, systems biology, and pharmaceutical research communities. This work will also contribute to developing novel strategies in the alteration of host-gut microbiota relationships which can in turn beneficially modulate the host metabolism.