Role of land use and seasonal factors in water quality degradation

Surface water and groundwater are the most important water sources in the natural environment. Land use and seasonal factors play an important role in influencing the quality of these water sources. An in-depth understanding of the role of these two influential factors can help to implement an effective catchment management strategy for the protection of these water sources. This paper discusses the outcomes of an extensive research study which investigated the role of land use and seasonal factors on surface water and groundwater pollution in a mixed land use coastal catchment. The study confirmed that the influence exerted on the water environment by seasonal factors is secondary to that of land use. Furthermore, the influence of land use and seasonal factors on surface water and groundwater quality varies with the pollutant species. This highlights the need to specifically take into consideration the targeted pollutants and the key influential factors for the effective protection of vulnerable receiving water environments.

Seasonal amplitude of hemorrhagic fever with renal syndrome in China : a call for attention to neglected regions

Hemorrhagic fever with renal syndrome (HFRS), a rodent-borne viral disease characterized by fever, hemorrhagic, kidney damage and hypotension, is caused by different species of hantaviruses [1]. Every year, HFRS affects thousands of people in Asia, and more than 90% of these cases are reported in China [2, 3]. Due to its high fatality, HFRS has attracted considerable research attention, and prior studies have predominantly focused on quantifying HFRS morbidity [4], identifying high risk areas [5] and populations [6], or exploring peak time of HFRS occurrence [3]. To date, no study has assessed the seasonal amplitude of HFRS in China, even though it reveals the seasonal fluctuation and thus may provide pivotal information on the possibility of HFRS outbreaks.

Outbreak detection algorithms for seasonal disease data : a case study using Ross River virus disease

Background Detection of outbreaks is an important part of disease surveillance. Although many algorithms have been designed for detecting outbreaks, few have been specifically assessed against diseases that have distinct seasonal incidence patterns, such as those caused by vector-borne pathogens. Methods We applied five previously reported outbreak detection algorithms to Ross River virus (RRV) disease data (1991-2007) for the four local government areas (LGAs) of Brisbane, Emerald, Redland and Townsville in Queensland, Australia. The methods used were the Early Aberration Reporting System (EARS) C1, C2 and C3 methods, negative binomial cusum (NBC), historical limits method (HLM), Poisson outbreak detection (POD) method and the purely temporal SaTScan analysis. Seasonally-adjusted variants of the NBC and SaTScan methods were developed. Some of the algorithms were applied using a range of parameter values, resulting in 17 variants of the five algorithms. Results The 9,188 RRV disease notifications that occurred in the four selected regions over the study period showed marked seasonality, which adversely affected the performance of some of the outbreak detection algorithms. Most of the methods examined were able to detect the same major events. The exception was the seasonally-adjusted NBC methods that detected an excess of short signals. The NBC, POD and temporal SaTScan algorithms were the only methods that consistently had high true positive rates and low false positive and false negative rates across the four study areas. The timeliness of outbreak signals generated by each method was also compared but there was no consistency across outbreaks and LGAs. Conclusions This study has highlighted several issues associated with applying outbreak detection algorithms to seasonal disease data. In lieu of a true gold standard, a quantitative comparison is difficult and caution should be taken when interpreting the true positives, false positives, sensitivity and specificity.

Seasonal factors influencing the failure of buried water reticulation pipes

While the use of environmental factors in the analysis and prediction of failures of buried reticulation pipes in cold environments has been the focus of extensive work, the same cannot be said for failures occurring on pipes in other (non-freezing) environments. A novel analysis of pipe failures in such an environment is the subject of this paper. An exploratory statistical analysis was undertaken, identifying a peak in failure rates during mid to late summer. This peak was found to correspond to a peak in the rate of circumferential failures, whilst the rate of longitudinal failures remained constant. Investigation into the effect of climate on failure rates revealed that the peak in failure rates occurs due to differential soil movement as the result of shrinkage in expansive soils.

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.

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.

Seasonal and spatial variations in rare earth elements to identify inter-aquifer linkages and recharge processes in an Australian catchment

With the aim of elucidating the seasonal behaviour of rare earth elements (REEs), surface and groundwaters were collected under dry and wet conditions in different hydrological units of the Teviot Brook catchment (Southeast Queensland, Australia). Sampled waters showed a large degree of variability in both REE abundance and normalised patterns. Overall REE abundance ranged over nearly three orders of magnitude, and was consistently lower in the sedimentary bedrock aquifer (18ppt<∑REE<477ppt) than in the other hydrological systems studied. Abundance was greater in springs draining rhyolitic rocks (∑REE=300 and 2054ppt) than in springs draining basalt ranges (∑REE=25 and 83ppt), yet was highly variable in the shallow alluvial groundwater (16ppt<∑REE<5294ppt) and, to a lesser extent, in streamwater (85ppt<∑REE<2198ppt). Generally, waters that interacted with different rock types had different REE patterns. In order to obtain an unbiased characterisation of REE patterns, the ratios between light and middle REEs (R(M/L)) and the ratios between middle and heavy REEs (R(H/M)) were calculated for each sample. The sedimentary bedrock aquifer waters had highly evolved patterns depleted in light REEs and enriched in middle and heavy REEs (0.17seasonal variations in REE patterns, the difference in ratios between dry and wet sampling campaigns was determined for each repeated sampling location. Contributions from the sedimentary bedrock water to the alluvium during the wet season were identified at two locations (increase from R(H/M)=0.03 and 0.35 to R(H/M)=0.62 and 0.89). The effect of recharge through fractured igneous rocks was also observed in two boreholes intercepting the sedimentary bedrock, where the freshly recharged waters likely contributed to the deeper groundwater flow during the wet season (decrease from R(M/L)=0.81 and 0.56 to R(M/L)=0.46 and 0.17). Results from this study suggest that REEs may be usefully applied as indicators of recharge processes and inter-aquifer mixing. They also underline the importance of conducting seasonal sampling campaigns to capture possible short-term variations in REE patterns and abundance, which is essential to enable a better understanding of hydrological and hydrochemical processes in complex geological settings

Regional and seasonal variation in airborne grass pollen levels between cities of Australia and New Zealand

Although grass pollen is widely regarded as the major outdoor aeroallergen source in Australia and New Zealand (NZ), no assemblage of airborne pollen data for the region has been previously compiled. Grass pollen count data collected at 14 urban sites in Australia and NZ over periods ranging from 1 to 17 years were acquired, assembled and compared, revealing considerable spatiotemporal variability. Although direct comparison between these data is problematic due to methodological differences between monitoring sites, the following patterns are apparent. Grass pollen seasons tended to have more than one peak from tropics to latitudes of 37°S and single peaks at sites south of this latitude. A longer grass pollen season was therefore found at sites below 37°S, driven by later seasonal end dates for grass growth and flowering. Daily pollen counts increased with latitude; subtropical regions had seasons of both high intensity and long duration. At higher latitude sites, the single springtime grass pollen peak is potentially due to a cooler growing season and a predominance of pollen from C3 grasses. The multiple peaks at lower latitude sites may be due to a warmer season and the predominance of pollen from C4 grasses. Prevalence and duration of seasonal allergies may reflect the differing pollen seasons across Australia and NZ. It must be emphasized that these findings are tentative due to limitations in the available data, reinforcing the need to implement standardized pollen-monitoring methods across Australasia. Furthermore, spatiotemporal differences in grass pollen counts indicate that local, current, standardized pollen monitoring would assist with the management of pollen allergen exposure for patients at risk of allergic rhinitis and asthma. © 2015 Springer Science+Business Media Dordrecht

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.

Latitudinal and seasonal effects on growth of the Australian eastern king prawn (Melicertus plebejus)

The growth of the Australian eastern king prawn (Melicertus plebejus) is understood in greater detail by quantifying the latitudinal effect. The latitudinal effect is the change in the species' growth rate during migration. Mark-recapture data (N = 1635, latitude 22.21 degrees S-34.00 degrees S) presents northerly movement of the eastern king prawn, with New South Wales prawns showing substantial average movement of 140 km (standard deviation: 176 km) north. A generalized von Bertalanffy growth model framework is used to incorporate the latitudinal effect together with the canonical seasonal effect. Applying this method to eastern king prawn mark-recapture data guarantees consistent estimates for the latitudinal and seasonal effects. For M. plebejus, it was found that growth rate peaks on 25 and 29 January for males and females, respectively; is at a minimum on 27 and 31 July, respectively; and that the shape parameter, k (per year), changes by -0.0236 and -0.0556 every 1 degree of latitude south increase for males and females, respectively.

Risk management strategies using seasonal climate forecasting in irrigated cotton production: a tale of stochastic dominance.

Decision-making in agriculture is carried out in an uncertain environment with farmers often seeking information to reduce risk. As a result of the extreme variability of rainfall and stream-flows in north-eastern Australia, water supplies for irrigated agriculture are a limiting factor and a source of risk. The present study examined the use of seasonal climate forecasting (SCF) when calculating planting areas for irrigated cotton in the northern Murray Darling Basin. Results show that minimising risk by adjusting plant areas in response to SCF can lead to significant gains in gross margin returns. However, how farmers respond to SCF is dependent on several other factors including irrigators’ attitude towards risk.

Effect of seasonal conditions on fleece weight and its components in merino sheep grazing Mitchell grass pasture in North West Queensland

SUMMARY Seasonal conditions in the pre to post natal period and selected periods before and during wool growth were described using climatic measures and estimates of the quality and quantity of pasture on offer derived from a validated pasture production model (GRASP). The variation in greasy and clean fleece weight, yield, staple length, fibre diameter, neck and side wrinkle score of Merinos grazing Mitchell grass in north west Queensland was explained in terms of these pasture and climatic measures and animal characteristics such as reproductive status, age and skin area. Multiple regression equations predicting clean and greasy fleece weight from the proportion of days in the wool growth period that the green pool in the pasture was less than one kg/ha, the percentage utilisation of the pasture, age, reproductive status and skin area of the ewes explained 87% and 79% of the variation respectively. Equations with similar predictors explained 58-85% of the variation of the other components. The inclusion of pasture conditions in the pre to post natal period did not significantly improve the predictions of the animal’s later performance. 22nd Biennial Conference.