Seasonal occurrence and distribution of Bryde's whales in the Hauraki Gulf, New Zealand

The Hauraki Gulf is a large, shallow embayment located north of Auckland City (36°51′S, 174°46′E), New Zealand. Bryde's whales (Balaenoptera edeni) are the most frequently observed balaenopterid in these waters. To assess the use of the Hauraki Gulf for this species, we examined the occurrence and distribution in relation to environmental parameters. Data were collected from a platform of opportunity during 674 daily surveys between March 2003 and February 2006. A total of 760 observations of Bryde's whales were recorded throughout the study period during 371 surveys. The number of Bryde's whales sighted/day was highest in winter, coinciding with the coolest median sea-surface temperature (14.6°C). Bryde's whales were recorded throughout the Hauraki Gulf in water depths ranging from 12.1–59.8 m (mean = 42.3, SD = 5.1). Cow–calf pairs were most frequently observed during the austral autumn in water depths of 29.9–53.9 m (mean = 40.8, SD = 5.2). Data from this study suggest Bryde's whales in the Hauraki Gulf exhibit a mix of both “inshore” and “offshore” characteristics from the Bryde's whales examined off the coast of South Africa. Based on complete mitochondrial DNA sequences, Sasaki et al. (2006) recognized two sister species of Bryde's whales: Balaenoptera brydei and B. edeni, with the latter including small-type, more coastal Bryde's whales from Japan, Hong Kong, and Australia. Their samples and samples in previous analyses of small-type whales, all originated from eastern and southeastern Asia. These authors did not include the forms of Bryde's whales that occur in other regions, e.g., in the Pacific off Peru (Valdivia et al. 1981), in the Atlantic off Brazil (Best 1977) and in the western Indian Ocean off South Africa (Best 1977). Recent genetic analysis using mtDNA from the “inshore” and “offshore” forms from South Africa confirms the offshore form is B. brydei, and establishes that the inshore form is more closely related to B. brydei than to B. edeni (Penry 2010). These different forms do vary considerably in their habitat use and ecology (refer to Table 1 for a detailed comparison between the South African inshore and offshore forms, as described by Best (1967, 1977) and the Bryde's whales from New Zealand (Wiseman 2008). Recent genetic analysis on the Bryde's whales in the Hauraki Gulf suggests they are B. brydei (Wiseman 2008). However, pending resolution of the uncertainty within and between species of this genus, we follow the Society of Marine Mammal's committee on taxonomy, who state that B. edeni applies to all Bryde's whales.

Soil moisture variability in a temperate deciduous forest: insights from electrical resistivity and throughfall data

Hydrogeophysics is a growing discipline that holds significant promise to help elucidate details of dynamic processes in the near surface, built on the ability of geophysical methods to measure properties from which hydrological and geochemical variables can be derived. For example, bulk electrical conductivity is governed by, amongst others, interstitial water content, fluid salinity, and temperature, and can be measured using a range of geophysical methods. In many cases, electrical resistivity tomography (ERT) is well suited to characterize these properties in multiple dimensions and to monitor dynamic processes, such as water infiltration and solute transport. In recent years, ERT has been used increasingly for ecosystem research in a wide range of settings; in particular to characterize vegetation-driven changes in root-zone and near-surface water dynamics. This increased popularity is due to operational factors (e.g., improved equipment, low site impact), data considerations (e.g., excellent repeatability), and the fact that ERT operates at scales significantly larger than traditional point sensors. Current limitations to a more widespread use of the approach include the high equipment costs, and the need for site-specific petrophysical relationships between properties of interest. In this presentation we will discuss recent equipment advances and theoretical and methodological aspects involved in the accurate estimation of soil moisture from ERT results. Examples will be presented from two studies in a temperate climate (Michigan, USA) and one from a humid tropical location (Tapajos, Brazil).

Hydrological consequences of land-cover change: Quantifying the influence of plants on soil moisture with time-lapse electrical resistivity

Electrical resistivity of soils and sediments is strongly influenced by the presence of interstitial water. Taking advantage of this dependency, electrical-resistivity imaging (ERI) can be effectively utilized to estimate subsurface soil-moisture distributions. The ability to obtain spatially extensive data combined with time-lapse measurements provides further opportunities to understand links between land use and climate processes. In natural settings, spatial and temporal changes in temperature and porewater salinity influence the relationship between soil moisture and electrical resistivity. Apart from environmental factors, technical, theoretical, and methodological ambiguities may also interfere with accurate estimation of soil moisture from ERI data. We have examined several of these complicating factors using data from a two-year study at a forest-grassland ecotone, a boundary between neighboring but different plant communities.At this site, temperature variability accounts for approximately 20-45 of resistivity changes from cold winter to warm summer months. Temporal changes in groundwater conductivity (mean=650 S/cm =57.7) and a roughly 100-S/cm spatial difference between the forest and grassland had only a minor influence on the moisture estimates. Significant seasonal fluctuations in temperature and precipitation had negligible influence on the basic measurement errors in data sets. Extracting accurate temporal changes from ERI can be hindered by nonuniqueness of the inversion process and uncertainties related to time-lapse inversion schemes. The accuracy of soil moisture obtained from ERI depends on all of these factors, in addition to empirical parameters that define the petrophysical soil-moisture/resistivity relationship. Many of the complicating factors and modifying variables to accurately quantify soil moisture changes with ERI can be accounted for using field and theoretical principles.

Inter-cycle variability of ignition delay in an ethanol fumigated common rail diesel engine

An experimental study has been performed to investigate the ignition delay of a modern heavy-duty common-rail diesel engine run with fumigated ethanol substitutions up to 40% on an energy basis. The ignition delay was determined through the use of statistical modelling in a Bayesian framework this framework allows for the accurate determination of the start of combustion from single consecutive cycles and does not require any differentiation of the in-cylinder pressure signal. At full load the ignition delay has been shown to decrease with increasing ethanol substitutions and evidence of combustion with high ethanol substitutions prior to diesel injection have also been shown experimentally and by modelling. Whereas, at half load increasing ethanol substitutions have increased the ignition delay. A threshold absolute air to fuel ratio (mole basis) of above ~110 for consistent operation has been determined from the inter-cycle variability of the ignition delay, a result that agrees well with previous research of other in-cylinder parameters and further highlights the correlation between the air to fuel ratio and inter-cycle variability. Numerical modelling to investigate the sensitivity of ethanol combustion has also been performed. It has been shown that ethanol combustion is sensitive to the initial air temperature around the feasible operating conditions of the engine. Moreover, a negative temperature coefficient region of approximately 900{1050 K (the approximate temperature at fuel injection) has been shown with for n-heptane and n-heptane/ethanol blends in the numerical modelling. A consequence of this is that the dominate effect influencing the ignition delay under increasing ethanol substitutions may rather be from an increase in chemical reactions and not from in-cylinder temperature. Further investigation revealed that the chemical reactions at low ethanol substitutions are different compared to the high (> 20%) ethanol substitutions.

Process variability of pollutant build-up on urban road surfaces

Knowledge of the pollutant build-up process is a key requirement for developing stormwater pollution mitigation strategies. In this context, process variability is a concept which needs to be understood in-depth. Analysis of particulate build-up on three road surfaces in an urban catchment confirmed that particles <150µm and >150µm have characteristically different build-up patterns, and these patterns are consistent over different field conditions. Three theoretical build-up patterns were developed based on the size-fractionated particulate build-up patterns, and these patterns explain the variability in particle behavior and the variation in particle-bound pollutant load and composition over the antecedent dry period. Behavioral variability of particles <150µm was found to exert the most significant influence on the build-up process variability. As characterization of process variability is particularly important in stormwater quality modeling, it is recommended that the influence of behavioral variability of particles <150µm on pollutant build-up should be specifically addressed. This would eliminate model deficiencies in the replication of the build-up process and facilitate the accounting of the inherent process uncertainty, and thereby enhance the water quality predictions.

Weather variability and influenza A (H7N9) transmission in Shanghai, China: A Bayesian spatial analysis

Abstract Background A novel avian influenza A (H7N9) virus was first found in humans in Shanghai, and infected over 433 patients in China. To date, very little is known about the spatiotemporal variability or environmental drivers of the risk of H7N9 infection. This study explored the spatial and temporal variation of H7N9 infection and assessed the effects of temperature and rainfall on H7N9 incidence. Methods A Bayesian spatial conditional autoregressive (CAR) model was used to assess the spatiotemporal distribution of the risk of H7N9 infection in Shanghai, by district and fortnight for the period 19th February–14th April 2013. Data on daily laboratory-confirmed H7N9 cases, and weather variability including temperature (°C) and rainfall (mm) were obtained from the Chinese Information System for Diseases Control and Prevention and Chinese Meteorological Data Sharing Service System, respectively, and aggregated by fortnight. Results High spatial variations in the H7N9 risk were mainly observed in the east and centre of Shanghai municipality. H7N9 incidence rate was significantly associated with fortnightly mean temperature (Relative Risk (RR): 1.54; 95% credible interval (CI): 1.22–1.94) and fortnightly mean rainfall (RR: 2.86; 95% CI: 1.47–5.56). Conclusion There was a substantial variation in the spatiotemporal distribution of H7N9 infection across different districts in Shanghai. Optimal temperature and rainfall may be one of the driving forces for H7N9.

Biophysical correlates of intrinsic and stress-induced morphological variability in lateral amygdaloid neurons: A computational study

Morphological and physiological characteristics of neurons located in the dorsolateral and two ventral subdivisions of the lateral amygdala (LA) have been compared in order to differentiate their roles in the formation and storage of fear memories (Alphs et al, SfN abs 623.1, 2003). Briefly, in these populations, significant differences are observed in input resistance, membrane time constant, firing frequency, dendritic tortuosity, numbers of primary dendrites, dendritic segments and dendritic nodes...

Improving out-domain PLDA speaker verification using unsupervised inter-dataset variability compensation approach

Experimental studies have found that when the state-of-the-art probabilistic linear discriminant analysis (PLDA) speaker verification systems are trained using out-domain data, it significantly affects speaker verification performance due to the mismatch between development data and evaluation data. To overcome this problem we propose a novel unsupervised inter dataset variability (IDV) compensation approach to compensate the dataset mismatch. IDV-compensated PLDA system achieves over 10% relative improvement in EER values over out-domain PLDA system by effectively compensating the mismatch between in-domain and out-domain data.

Influence of pollutant build-up on variability in wash-off from urban road surfaces

Variability in the pollutant wash-off process is a concept which needs to be understood in-depth in order to better assess the outcomes of stormwater quality models, and thereby strengthen stormwater pollution mitigation strategies. Current knowledge about the wash-off process does not extend to a clear understanding of the influence of the initially available pollutant build-up on the variability of the pollutant wash-off load and composition. Consequently, pollutant wash-off process variability is poorly characterised in stormwater quality models, which can result in inaccurate stormwater quality predictions. Mathematical simulation of particulate wash-off from three urban road surfaces confirmed that the wash-off load of particle size fractions <150µm and >150µm after a storm event vary with the build-up of the respective particle size fractions available at the beginning of the storm event. Furthermore, pollutant load and composition associated with the initially available build-up of <150µm particles predominantly influence the variability in washed-off pollutant load and composition. The influence of the build-up of pollutants associated with >150µm particles on wash-off process variability is significant only for relatively shorter duration storm events.

Seasonal variations of outdoor air pollution and factors driving them in the school environment in rural Bhutan

A quantitative understanding of outdoor air quality in school environments is crucial given that air pollution levels inside classrooms are significantly influenced by outdoor pollution sources. To date, only a handful of studies have been conducted on this important topic in developing countries. The aim of this study was to quantify pollutant levels in the outdoor environment of a school in Bhutan and assess the factors driving them. Measurements were conducted for 16 weeks, spanning the wet and dry seasons, in a rural school in Bhutan. PM10, PM2.5, particle number (PN) and CO were measured daily using real-time instruments, while weekly samples for volatile organic compounds (VOCs), carbonyls and NO2 were collected using a passive sampling method. Overall mean PM10 and PM2.5 concentrations (µg/m3) were 27 and 13 for the wet, and 36 and 29 for the dry season, respectively. Only wet season data were available for PN concentrations, with a mean of 2.56 × 103 particles/cm3. Mean CO concentrations were below the detection limit of the instrumentation for the entire measurement period. Only low levels of eight VOCs were detected in both the wet and dry seasons, which presented different seasonal patterns in terms of the concentration of different compounds. The notable carbonyls were formaldehyde and hexaldehyde, with mean concentrations (µg/m3) of 2.37 and 2.41 for the wet, and 6.22 and 0.34 for the dry season, respectively. Mean NO2 cocentration for the dry season was 1.7 µg/m3, while it was below the detection limit of the instrumentation for the wet season. The pollutant concentrations were associated with a number of factors, such as cleaning and combustion activities in and around the school. A comparison with other school studies showed comparable results with a few of the studies, but in general, we found lower pollutant concentrations in the present study.

Mapping the regional influence of genetics on brain structure variability - A Tensor-Based Morphometry study

Genetic and environmental factors influence brain structure and function profoundly. The search for heritable anatomical features and their influencing genes would be accelerated with detailed 3D maps showing the degree to which brain morphometry is genetically determined. As part of an MRI study that will scan 1150 twins, we applied Tensor-Based Morphometry to compute morphometric differences in 23 pairs of identical twins and 23 pairs of same-sex fraternal twins (mean age: 23.8 ± 1.8 SD years). All 92 twins' 3D brain MRI scans were nonlinearly registered to a common space using a Riemannian fluid-based warping approach to compute volumetric differences across subjects. A multi-template method was used to improve volume quantification. Vector fields driving each subject's anatomy onto the common template were analyzed to create maps of local volumetric excesses and deficits relative to the standard template. Using a new structural equation modeling method, we computed the voxelwise proportion of variance in volumes attributable to additive (A) or dominant (D) genetic factors versus shared environmental (C) or unique environmental factors (E). The method was also applied to various anatomical regions of interest (ROIs). As hypothesized, the overall volumes of the brain, basal ganglia, thalamus, and each lobe were under strong genetic control; local white matter volumes were mostly controlled by common environment. After adjusting for individual differences in overall brain scale, genetic influences were still relatively high in the corpus callosum and in early-maturing brain regions such as the occipital lobes, while environmental influences were greater in frontal brain regions that have a more protracted maturational time-course.

Incorporating process variability into stormwater quality modelling

Process variability in pollutant build-up and wash-off generates inherent uncertainty that affects the outcomes of stormwater quality models. Poor characterisation of process variability constrains the accurate accounting of the uncertainty associated with pollutant processes. This acts as a significant limitation to effective decision making in relation to stormwater pollution mitigation. The study undertaken developed three theoretical scenarios based on research findings that variations in particle size fractions <150µm and >150µm during pollutant build-up and wash-off primarily determine the variability associated with these processes. These scenarios, which combine pollutant build-up and wash-off processes that takes place on a continuous timeline, are able to explain process variability under different field conditions. Given the variability characteristics of a specific build-up or wash-off event, the theoretical scenarios help to infer the variability characteristics of the associated pollutant process that follows. Mathematical formulation of the theoretical scenarios enables the incorporation of variability characteristics of pollutant build-up and wash-off processes in stormwater quality models. The research study outcomes will contribute to the quantitative assessment of uncertainty as an integral part of the interpretation of stormwater quality modelling outcomes.

Bahia grass pollen specific IgE is common in seasonal rhinitis patients but has limited cross-reactivity with Ryegrass

Background: Perennial Ryegrass is a major cause of rhinitis in spring and early summer. Bahia grass, Paspalum notatum, flowers late into summer and could account for allergic rhinitis at this time. We determined the frequency of serum immunoglobulin (Ig)E reactivity with Bahia grass in Ryegrass pollen allergic patients and investigated IgE cross-reactivity between Bahia and Ryegrass. Methods: Serum from 33 Ryegrass pollen allergic patients and 12 nonatopic donors were tested for IgE reactivity with Bahia and Ryegrass pollen extracts (PE) by enzyme-linked immunosorbent assay (ELISA), western blotting and inhibition ELISA. Allergen-specific antibodies from a pool of sera from allergic donors were affinity purified and tested for IgE cross-reactivity. Results: Seventy-eight per cent of the sera had IgE reactivity with Bahia grass, but more weakly than with Ryegrass. Antibodies eluted from the major Ryegrass pollen allergens, Lol p 1 and Lol p 5, showed IgE reactivity with allergens of Ryegrass and Canary but not Bahia or Bermuda grasses. Timothy, Canary and Ryegrass inhibited IgE reactivity with Ryegrass and Bahia grass, whereas Bahia, Johnson and Bermuda grass did not inhibit IgE reactivity with Ryegrass. Conclusions: The majority of Ryegrass allergic patients also showed serum IgE reactivity with Bahia grass PE. However, Bahia grass and Ryegrass had only limited IgE cross-reactivity indicating that Bahia grass should be considered in diagnosis and treatment of patients with hay fever late in' the grass pollen season.

VH gene usage in immunoglobulin E responses of seasonal rhinitis patients allergic to grass pollen is oligoclonal and antigen driven

Background: IgE is the pivotal-specific effector molecule of allergic reactions yet it remains unclear whether the elevated production of IgE in atopic individuals is due to superantigen activation of B cell populations, increased antibody class switching to IgE or oligoclonal allergen-driven IgE responses. Objectives: To increase our understanding of the mechanisms driving IgE responses in allergic disease we examined immunoglobulin variable regions of IgE heavy chain transcripts from three patients with seasonal rhinitis due to grass pollen allergy. Methods: Variable domain of heavy chain-epsilon constant domain 1 cDNAs were amplified from peripheral blood using a two-step semi-nested PCR, cloned and sequenced. Results: The VH gene family usage in subject A was broadly based, but there were two clusters of sequences using genes VH 3-9 and 3-11 with unusually low levels of somatic mutations, 0-3%. Subject B repeatedly used VH 1-69 and subject C repeatedly used VH 1-02, 1-46 and 5a genes. Most clones were highly mutated being only 86-95% homologous to their germline VH gene counterparts and somatic mutations were more abundant at the complementarity determining rather than framework regions. Multiple sequence alignment revealed both repeated use of particular VH genes as well as clonal relatedness among clusters of IgE transcripts. Conclusion: In contrast to previous studies we observed no preferred VH gene common to IgE transcripts of the three subjects allergic to grass pollen. Moreover, most of the VH gene characteristics of the IgE transcripts were consistent with oligoclonal antigen-driven IgE responses.