Reliability of vegetation community information derived using decorana ordination and fuzzy c-means clustering

Descriptions of vegetation communities are often based on vague semantic terms describing species presence and dominance. For this reason, some researchers advocate the use of fuzzy sets in the statistical classification of plant species data into communities. In this study, spatially referenced vegetation abundance values collected from Greek phrygana were analysed by ordination (DECORANA), and classified on the resulting axes using fuzzy c-means to yield a point data-set representing local memberships in characteristic plant communities. The fuzzy clusters matched vegetation communities noted in the field, which tended to grade into one another, rather than occupying discrete patches. The fuzzy set representation of the community exploited the strengths of detrended correspondence analysis while retaining richer information than a TWINSPAN classification of the same data. Thus, in the absence of phytosociological benchmarks, meaningful and manageable habitat information could be derived from complex, multivariate species data. We also analysed the influence of the reliability of different surveyors' field observations by multiple sampling at a selected sample location. We show that the impact of surveyor error was more severe in the Boolean than the fuzzy classification. © 2007 Springer.

Self-affinity in financial asset returns

We test for departures from normal and independent and identically distributed (NIID) log returns, for log returns under the alternative hypothesis that are self-affine and either long-range dependent, or drawn randomly from an L-stable distribution with infinite higher-order moments. The finite sample performance of estimators of the two forms of self-affinity is explored in a simulation study. In contrast to rescaled range analysis and other conventional estimation methods, the variant of fluctuation analysis that considers finite sample moments only is able to identify both forms of self-affinity. When log returns are self-affine and long-range dependent under the alternative hypothesis, however, rescaled range analysis has higher power than fluctuation analysis. The techniques are illustrated by means of an analysis of the daily log returns for the indices of 11 stock markets of developed countries. Several of the smaller stock markets by capitalization exhibit evidence of long-range dependence in log returns. © 2012 Elsevier Inc. All rights reserved.

Diatom abundance in surface sediments of the Southern Ocean

Based on the quantitative analysis of diatom assemblages preserved in 274 surface sediment samples recovered in the Pacific, Atlantic and western Indian sectors of the Southern Ocean we have defined a new reference database for quantitative estimation of late-middle Pleistocene Antarctic sea ice fields using the transfer function technique. The Detrended Canonical Analysis (DCA) of the diatom data set points to a unimodal distribution of the diatom assemblages. Canonical Correspondence Analysis (CCA) indicates that winter sea ice (WSI) but also summer sea surface temperature (SSST) represent the most prominent environmental variables that control the spatial species distribution. To test the applicability of transfer functions for sea ice reconstruction in terms of concentration and occurrence probability we applied four different methods, the Imbrie and Kipp Method (IKM), the Modern Analog Technique (MAT), Weighted Averaging (WA), and Weighted Averaging Partial Least Squares (WAPLS), using logarithm-transformed diatom data and satellite-derived (1981-2010) sea ice data as a reference. The best performance for IKM results was obtained using a subset of 172 samples with 28 diatom taxa/taxa groups, quadratic regression and a three-factor model (IKM-D172/28/3q) resulting in root mean square errors of prediction (RMSEP) of 7.27% and 11.4% for WSI and summer sea ice (SSI) concentration, respectively. MAT estimates were calculated with different numbers of analogs (4, 6) using a 274-sample/28-taxa reference data set (MAT-D274/28/4an, -6an) resulting in RMSEP's ranging from 5.52% (4an) to 5.91% (6an) for WSI as well as 8.93% (4an) to 9.05% (6an) for SSI. WA and WAPLS performed less well with the D274 data set, compared to MAT, achieving WSI concentration RMSEP's of 9.91% with WA and 11.29% with WAPLS, recommending the use of IKM and MAT. The application of IKM and MAT to surface sediment data revealed strong relations to the satellite-derived winter and summer sea ice field. Sea ice reconstructions performed on an Atlantic- and a Pacific Southern Ocean sediment core, both documenting sea ice variability over the past 150,000 years (MIS 1 - MIS 6), resulted in similar glacial/interglacial trends of IKM and MAT-based sea-ice estimates. On the average, however, IKM estimates display smaller WSI and slightly higher SSI concentration and probability at lower variability in comparison with MAT. This pattern is a result of different estimation techniques with integration of WSI and SSI signals in one single factor assemblage by applying IKM and selecting specific single samples, thus keeping close to the original diatom database and included variability, by MAT. In contrast to the estimation of WSI, reconstructions of past SSI variability remains weaker. Combined with diatom-based estimates, the abundance and flux pattern of biogenic opal represents an additional indication for the WSI and SSI extent.

Benthic foraminifera asemblages and isotopic composition of surface sediment samples off Morocco

The influence of different primary productivity regimes on live (Rose Bengal stained) and dead benthic foraminiferal distribution, as well as on the stable carbon isotopic composition of foraminiferal tests, was investigated in sediment surface samples (0-1 cm) from the upwelling region off Morocco between Cape Ghir (31°N) and Cape Yubi (27°N). A combination of factor analysis, detrended correspondence analysis (DCA) and canonical correspondence analysis (CCA) was applied to the benthic foraminiferal data sets. Five major assemblages for both the live and dead fauna were revealed by factor analysis. In the cape regions organic matter fluxes are enhanced by high chlorophyll-a concentrations in the overlying surface waters. Here, benthic foraminiferal faunas are characterized by identical live and dead assemblages, high standing stocks, and low species delta13C values, indicating constant year-round high productivity. Bulimina marginata dominates the unique fauna at the shallowest station off Cape Ghir indicating highest chlorophyll-a concentrations. Off both capes, the succession of the Bulimina aculeata/Uvigerina mediterranea assemblage, the Sphaeroidina bulloides/Gavelinopsis translucens assemblage, and the Hoeglundina elegans assemblage from the shelf to the deep sea reflects the decrease in chlorophyll-a concentrations, hence the export flux. In contrast, the area between the capes is characterized by differently composed live and dead assemblages, low standing stocks, and less depleted delta13C values, thus reflecting low primary productivity. High foraminiferal numbers of Epistominella exigua, Eponides pusillus, and Globocassidulina subglobosa in the dead fauna indicate a seasonally varying primary productivity signal. Significantly lower mean delta13C values were recorded in Bulimina mexicana, Cibicidoides kullenbergi, H. elegans, U. mediterranea and Uvigerina peregrina. Cibicidoides wuellerstorfi is a faithful recorder of bottom water delta13C in the Canary Islands regions. The mean delta13C signal of this species is not significantly influenced by constant high organic matter fluxes. The species-specific offset between live and dead specimens is the same.

Lacustrine Arcellinina (Testate Amoebae) as Bioindicators of Arsenic Contamination

Arcellininids (testate amoebae) were examined from 61 surface sediment samples collected from 59 lakes in the vicinity of former gold mines, notably Giant Mine, near Yellowknife, Northwest Territories, Canada to determine their utility as bioindicators of arsenic (As), which occurs both as a byproduct of gold extraction at mines in the area and ore-bearing outcrops. Cluster analysis (Q-R-mode) and detrended correspondence analysis (DCA) reveal five arcellininid assemblages, three of which are related to varying As concentrations in the sediment samples. Redundancy analysis (RDA) showed that 14 statistically significant environmental parameters explained 57 % of the variation in faunal distribution, while partial RDA indicated that As had the greatest influence on assemblage variance (10.7 %; p < 0.10). Stress-indicating species (primarily centropyxids) characterized the faunas of samples with high As concentrations (median = 121.7 ppm, max > 10000 ppm, min = 16.1 ppm, n = 32), while difflugiid dominated assemblages were prevalent in substrates with relatively low As concentrations (median = 30.2 ppm, max = 905.2 ppm, min = 6.3 ppm, n = 20). Most of the lakes with very high As levels are located downwind (N and W) of the former Giant Mine roaster stack where refractory ore was roasted and substantial quantities of As were released (as As2O3) to the atmosphere in the first decade of mining. This spatial pattern suggests that a significant proportion of the observed As, in at least these lakes, are industrially derived. The results of this study highlight the sensitivity of Arcellinina to As and confirm that the group has considerable potential for assessing the impact of As contamination on lakes.

DIFFERENTIATION OF ARBOREAL VEGETATION IN THREE SECTORS OF A FOREST FRAGMENT RELATED TO ITS HISTORICAL DISTURBANCES

Forest fragmentation is one of the main causes of biodiversity loss, directly affecting the ecological processes. This study aimed to evaluate tree diversity, structure, and composition parameters in three sectors of a forest fragment with distinct disturbance records. The arboreal vegetation was evaluated in twenty-four 10 × 10 m plots, sampling a total of 1,228 living individuals. We calculated Shanon’s diversity index, Pielou’s equability, and jackknife estimators of first and second orders. The sampled individuals were distributed in diameter classes and the importance value (VI) was calculated for each species. It was made a Detrended Correspondence Analysis (DCA) to verify whether there were significant distinctions between the sectors. It was noticed that the sector where there was clear cutting and vegetation burning in a recent past had higher abundance and richness but also the worst equability. That corresponds to the effects of perturbation as confirmed by the tree diameters and the presence of species of greater importance value. The sector that had no record of disturbance, situated in a location with greater variety of microenvironments, presented diversity, structure, and composition consistent with a no disturbance scenario. The other sector, which did not have clear cutting, was subjected to cattle trampling presented ecological parameters consistent with the absence of major disturbances. On the other hand, this third sector had the smallest environmental diversity, which puts this last sector in an intermediate situation.

Roślinność wodna, błotna i bagienna północnej części Dolnych Łużyc

Wydział Biologii

Analysis of confinement potential fluctuation and band-gap renormalization effects on excitonic transition in GaAs/AlGaAs multiquantum wells grown on (100) and (311)A GaAs surfaces

The competition between confinement potential fluctuations and band-gap renormalization (BGR) in GaAs/AlxGa1-xAs quantum wells grown on [1 0 0] and [3 1 1]A GaAs substrates is evaluated. The results clearly demonstrate the coexistence of the band-tail states filling related to potential fluctuations and the band-gap renormalization caused by an increase in the density of photogenerated carriers during the photoluminescence (PL) experiments. Both phenomena have strong influence on temperature dependence of the PL-peak energy (E-PL(T)). As the photon density increases, the E-PL can shift to either higher or lower energies, depending on the sample temperature. The temperature at which the displacement changes from a blueshift to a redshift is governed by the magnitude of the potential fluctuations and by the variation of BGR with excitation density. A simple band-tail model with a Gaussian-like distribution of the density of state was used to describe the competition between the band-tail filling and the BGR effects on E-PL(T). (C) 2012 Elsevier B.V. All rights reserved.

Geophysical Analysis of Seasonal Montandon Gravel Ridge Water Table Fluctuation and Moisture Gradient Variation due to Storm Events

The purpose of this research project is to continue exploring the Montandon Long-Term Hydrologic Research Site(LTHR) by using multiple geophysical methods to obtain more accurate and precise information regarding subsurface hydrologic properties of a local gravel ridge,which are important to both the health of surrounding ecosystems and local agriculture. Through using non-invasive geophysical methods such as seismic refraction, Direct Current resistivity and ground penetrating radar (GPR) instead of invasive methods such as boreholedrilling which displace sediment and may alter water flow, data collection is less likely to bias the data itself. In addition to imaging the gravel ridge subsurface, another important researchpurpose is to observe how both water table elevation and the moisture gradient (moisture content of the unsaturated zone) change over a seasonal time period and directly after storm events. The combination of three types of data collection allows the strengths of each method combine together and provide a relatively strongly supported conclusions compared to previous research. Precipitation and geophysical data suggest that an overall increase in precipitation during the summer months causes a sharp decrease in subsurface resistivity within the unsaturated zone. GPR velocity data indicate significant immediate increase in moisture content within the shallow vadose zone (< 1m), suggesting that rain water was infiltrating into the shallow subsurface. Furthermore, the combination of resistivity and GPR results suggest that the decreased resistivity within the shallow layers is due to increased ion content within groundwater. This is unexpected as rainwater is assumed to have a DC resistivity value of 3.33*105 ohm-m. These results may suggest that ions within the sediment must beincorporated into the infiltrating water.

Intelligent reliability analysis with incomplete covariates

The reliability analysis is crucial to reducing unexpected down time, severe failures and ever tightened maintenance budget of engineering assets. Hazard based reliability methods are of particular interest as hazard reflects the current health status of engineering assets and their imminent failure risks. Most existing hazard models were constructed using the statistical methods. However, these methods were established largely based on two assumptions: one is the assumption of baseline failure distributions being accurate to the population concerned and the other is the assumption of effects of covariates on hazards. These two assumptions may be difficult to achieve and therefore compromise the effectiveness of hazard models in the application. To address this issue, a non-linear hazard modelling approach is developed in this research using neural networks (NNs), resulting in neural network hazard models (NNHMs), to deal with limitations due to the two assumptions for statistical models. With the success of failure prevention effort, less failure history becomes available for reliability analysis. Involving condition data or covariates is a natural solution to this challenge. A critical issue for involving covariates in reliability analysis is that complete and consistent covariate data are often unavailable in reality due to inconsistent measuring frequencies of multiple covariates, sensor failure, and sparse intrusive measurements. This problem has not been studied adequately in current reliability applications. This research thus investigates such incomplete covariates problem in reliability analysis. Typical approaches to handling incomplete covariates have been studied to investigate their performance and effects on the reliability analysis results. Since these existing approaches could underestimate the variance in regressions and introduce extra uncertainties to reliability analysis, the developed NNHMs are extended to include handling incomplete covariates as an integral part. The extended versions of NNHMs have been validated using simulated bearing data and real data from a liquefied natural gas pump. The results demonstrate the new approach outperforms the typical incomplete covariates handling approaches. Another problem in reliability analysis is that future covariates of engineering assets are generally unavailable. In existing practices for multi-step reliability analysis, historical covariates were used to estimate the future covariates. Covariates of engineering assets, however, are often subject to substantial fluctuation due to the influence of both engineering degradation and changes in environmental settings. The commonly used covariate extrapolation methods thus would not be suitable because of the error accumulation and uncertainty propagation. To overcome this difficulty, instead of directly extrapolating covariate values, projection of covariate states is conducted in this research. The estimated covariate states and unknown covariate values in future running steps of assets constitute an incomplete covariate set which is then analysed by the extended NNHMs. A new assessment function is also proposed to evaluate risks of underestimated and overestimated reliability analysis results. A case study using field data from a paper and pulp mill has been conducted and it demonstrates that this new multi-step reliability analysis procedure is able to generate more accurate analysis results.

Probabilistic power system contingency analysis considering wind

This thesis was a step forward in developing probabilistic assessment of power system response to faults subject to intermittent generation by renewable energy. It has investigated the wind power fluctuation effect on power system stability, and the developed fast estimation process has demonstrated the feasibility for real-time implementation. A better balance between power network security and efficiency can be achieved based on this research outcome.

Turbulence measurements in a shallow tidal estuary : analysis based on triple decomposition

In an estuary, mixing and dispersion are the result of the combination of large scale advection and small scale turbulence which are both complex to estimate. A field study was conducted in a small sub-tropical estuary in which high frequency (50 Hz) turbulent data were recorded continuously for about 48 hours. A triple decomposition technique was introduced to isolate the contributions of tides, resonance and turbulence in the flow field. A striking feature of the data set was the slow fluctuations which exhibited large amplitudes up to 50% the tidal amplitude under neap tide conditions. The triple decomposition technique allowed a characterisation of broader temporal scales of high frequency fluctuation data sampled during a number of full tidal cycles.

Quantum-Ohmic Resistance Fluctuation In Disordered Conductors - An Invariant Imbedding Approach

It is now well known that in extreme quantum limit, dominated by the elastic impurity scattering and the concomitant quantum interference, the zero-temperature d.c. resistance of a strictly one-dimensional disordered system is non-additive and non-self-averaging. While these statistical fluctuations may persist in the case of a physically thin wire, they are implicitly and questionably ignored in higher dimensions. In this work, we have re-examined this question. Following an invariant imbedding formulation, we first derive a stochastic differential equation for the complex amplitude reflection coefficient and hence obtain a Fokker-Planck equation for the full probability distribution of resistance for a one-dimensional continuum with a Gaussian white-noise random potential. We then employ the Migdal-Kadanoff type bond moving procedure and derive the d-dimensional generalization of the above probability distribution, or rather the associated cumulant function –‘the free energy’. For d=3, our analysis shows that the dispersion dominates the mobilitly edge phenomena in that (i) a one-parameter B-function depending on the mean conductance only does not exist, (ii) an approximate treatment gives a diffusion-correction involving the second cumulant. It is, however, not clear whether the fluctuations can render the transition at the mobility edge ‘first-order’. We also report some analytical results for the case of the one dimensional system in the presence of a finite electric fiekl. We find a cross-over from the exponential to the power-low length dependence of resistance as the field increases from zero. Also, the distribution of resistance saturates asymptotically to a poissonian form. Most of our analytical results are supported by the recent numerical simulation work reported by some authors.

Eddy diffusivity: A single dispersion analysis of high resolution drifters in a tidal shallow estuary

In an estuary, mixing and dispersion resulting from turbulence and small scale fluctuation has strong spatio-temporal variability which cannot be resolved in conventional hydrodynamic models while some models employs parameterizations large water bodies. This paper presents small scale diffusivity estimates from high resolution drifters sampled at 10 Hz for periods of about 4 hours to resolve turbulence and shear diffusivity within a tidal shallow estuary (depth < 3 m). Taylor's diffusion theorem forms the basis of a first order estimate for the diffusivity scale. Diffusivity varied between 0.001 – 0.02 m2/s during the flood tide experiment. The diffusivity showed strong dependence (R2 > 0.9) on the horizontal mean velocity within the channel. Enhanced diffusivity caused by shear dispersion resulting from the interaction of large scale flow with the boundary geometries was observed. Turbulence within the shallow channel showed some similarities with the boundary layer flow which include consistency with slope of 5/3 predicted by Kolmogorov's similarity hypothesis within the inertial subrange. The diffusivities scale locally by 4/3 power law following Okubo's scaling and the length scale scales as 3/2 power law of the time scale. The diffusivity scaling herein suggests that the modelling of small scale mixing within tidal shallow estuaries can be approached from classical turbulence scaling upon identifying pertinent parameters.

Theoretical and Computational Analysis of Static and Dynamic Anomalies in Water-DMSO Binary Mixture at Low DMSO Concentrations

Experiments have repeatedly observed both thermodynamic and dynamic anomalies in aqueous binary mixtures, surprisingly at low solute concentration. Examples of such binary mixtures include water-DMSO, water-ethanol, water-tertiary butyl alcohol (TBA), and water-dioxane, to name a few. The anomalies have often been attributed to the onset of a structural transition, whose nature, however, has been left rather unclear. Here we study the origin of such anomalies using large scale computer simulations and theoretical analysis in water-DMSO binary mixture. At very low DMSO concentration (below 10%), small aggregates of DMSO are solvated by water through the formation of DMSO-(H2O)(2) moieties. As the concentration is increased beyond 10-12% of DMSO, spanning clusters comprising the same moieties appear in the system. Those clusters are formed and stabilized not only through H-bonding but also through the association of CH3 groups of DMSO. We attribute the experimentally observed anomalies to a continuum percolation-like transition at DMSO concentration X-DMSO approximate to 12-15%. The largest cluster size of CH3-CH3 aggregation clearly indicates the formation of such percolating clusters. As a result, a significant slowing down is observed in the decay of associated rotational auto time correlation functions (of the S = O bond vector of DMSO and O-H bond vector of water). Markedly unusual behavior in the mean square fluctuation of total dipole moment again suggests a structural transition around the same concentration range. Furthermore, we map our findings to an interacting lattice model which substantiates the continuum percolation model as the reason for low concentration anomalies in binary mixtures where the solutes involved have both hydrophilic and hydrophobic moieties.