Seasonal variation in rates of sporocyst and metacercarial infection by Brachylaima cribbi in helicid and hygromiid land snails on the Yorke Peninsula, South Australia

2005 ◽  
Vol 53 (6) ◽  
pp. 375 ◽  
Author(s):  
A. R. Butcher ◽  
D. I. Grove
Keyword(s):  
Seasonal Variation ◽  
Seasonal Variations ◽  
Infected Snail ◽  
South Australia ◽  
Land Snails ◽  
Infection Rates ◽  
Intermediate Hosts ◽  
Trematode Parasite ◽  
Yorke Peninsula ◽  
Theba Pisana

Brachylaima cribbi is a terrestrial trematode parasite of humans and other mammals, birds and reptiles, with helicid and hygromiid summer-aestivating land snails acting as first and second intermediate hosts. Beginning in April, seasonal variations in rates of sporocyst and metacercarial infection by B. cribbi were studied in Cochlicella acuta, Cernuella virgata and Theba pisana over 1 year at four ecologically diverse sites on the Yorke Peninsula, South Australia. The overall mean sporocyst prevalence rate in April was 2.7%. Sporocyst prevalences peaked during spring (10–78% for C. acuta, 12–44% for C. virgata and 10–18% for T. pisana). Metacercarial infection rates varied markedly from 10% to 98% at the start of the study. Overall metacercarial infection rates peaked with winter rains for T. pisana (average 50% infected) and in spring for C. acuta and C. virgata (average 80% infected) then declined in summer for all species. The average numbers of metacercariae per infected snail over the study period were 5.4 for C. virgata, 3.9 for C. acuta and 2.2 for T. pisana, with maximum numbers in winter or spring. Conditions on the Yorke Peninsula favour hyperinfection with this parasite.

The population dynamics of the mediterranean snails Cernuella virgata, Cochlicella acuta (Hygromiidae) and Theba pisana (Helicidae) in pasture - cereal rotations in South Australia: a 20-year study

2008 ◽  
Vol 48 (12) ◽  
pp. 1514 ◽  
Author(s):  
G. H. Baker
Keyword(s):  
Population Dynamics ◽  
Near Field ◽  
South Australia ◽  
Habitat Choice ◽  
Snail Species ◽  
Large Numbers ◽  
Yorke Peninsula ◽  
Sampling Scale ◽  
Theba Pisana ◽  
Peak Abundance

The snails Cernuella virgata, Cochlicella acuta and Theba pisana are introduced pests of grain crops and pastures in southern Australia. The population dynamics of these three species of snail were studied for 20 years in two adjacent fields where they coexisted on a farm on the Yorke Peninsula in South Australia. The fields were used for pasture–cereal rotations. Surveys were conducted in autumn and spring each year, coinciding respectively with the start of the breeding season and peak abundance of snails (mostly juveniles). Populations varied greatly in abundance between years and between species, but snails were generally most common in spring, in wet years, especially those with wet autumns and wet springs. Rainfall early in a particular year (i.e. at sowing of crops in autumn) can thus be used to predict the likelihood of heavy snail infestations later in spring (i.e. at harvest). In contrast, the abundance of adult snails in autumn was a poor predictor of the subsequent abundance of juvenile snails in spring, especially in crops. There were no significant correlations, at field scale, between the average abundance of the three species of snail in spring, in either pastures or crops. However, at a sampling scale of 0.25 m2, there were consistent, negative relationships between the abundance of all three snail species. Such patterns may reflect either competitive interactions between snails or subtle differences in micro-habitat choice. Patterns in the abundance of snails (e.g. large numbers near field edges) were suggestive of occasional invasion from dense populations in adjacent fields.

Children, snails and worms: the Brachylaima cribbi story

2016 ◽  
Vol 37 (1) ◽  
pp. 30 ◽  
Author(s):  
Andrew R Butcher
Keyword(s):  
Life Cycle ◽  
South America ◽  
South Australia ◽  
Land Snails ◽  
Intermediate Hosts ◽  
Larval Stages ◽  
Wide Range ◽  
Terrestrial Life ◽  
North And South America ◽  
North And South

Brachylaimids are parasitic trematode fluke worms that have a terrestrial life cycle involving land snails and slugs as the first and/or second intermediate hosts for the cercarial and metacercarial larval stages. A wide range of mammals, birds, reptiles and amphibians are the definitive hosts for the adult worm. Brachylaima spp. have been reported from most continents including Europe, Africa, Asia, North and South America and Australia. There are over 70 described species in the genus with seven species indigenous to Australia. Although Brachylaima spp. are a cosmopolitan terrestrial trematode they have not been recorded to infect humans other than the three Brachylaima cribbi infections reported in two children and an adult from South Australia.

Interactions between the land snails Theba pisana and Cernuella virgata in the laboratory

2020 ◽  
Author(s):  
Geoff H Baker
Keyword(s):  
Laboratory Experiments ◽  
Distribution Patterns ◽  
Land Snails ◽  
Snail Species ◽  
Agricultural Pests ◽  
Large Numbers ◽  
Small Scales ◽  
Novel Method ◽  
Theba Pisana ◽  
Inhibitory Components

ABSTRACT Two Mediterranean snails, Theba pisana and Cernuella virgata, are agricultural pests in southern Australia. The two species are rarely found together in large numbers in the field, at small scales (<1 m2). In laboratory experiments, the presence of T. pisana reduced the survival of C. virgata, but only when food (carrot + lettuce) was provided. When C. virgata was exposed to only the mucus trails and faeces of T. pisana, produced while feeding on lettuce, both the survival and activity of C. virgata were reduced. When carrot was substituted for lettuce, there was less effect. In addition, when C. virgata was exposed to T. pisana’s faeces only, derived from access to a mix of lettuce and carrot, there was no effect on C. virgata’s survival. The observed reductions in the survival of C. virgata were stronger in autumn (the breeding season for both snail species) compared with spring. Inhibitory components within the mucus trails of T. pisana may (1) help explain the observed distribution patterns of the two species at small scales in the field and (2) provide a novel method for control of pest populations of C. virgata, in some situations.

Hosts of the exotic ornate kangaroo tick, Amblyomma triguttatum triguttatum Koch, on southern Yorke Peninsula, South Australia

2007 ◽  
Vol 101 (5) ◽  
pp. 1323-1330 ◽  
Author(s):  
Helen P. Waudby ◽  
Sophie Petit ◽  
Bruce Dixon ◽  
Ross H. Andrews
Keyword(s):  
South Australia ◽  
Yorke Peninsula

Global mapping of seasonal variations in tides from tide gauge and satellite altimeter data

2021 ◽  
Author(s):  
Inger Bij de Vaate ◽  
Henrique Guarneri ◽  
Cornelis Slobbe ◽  
Martin Verlaan
Keyword(s):  
Seasonal Variation ◽  
Sea Level ◽  
Seasonal Variations ◽  
Large Scale ◽  
Arctic Region ◽  
The Arctic ◽  
Altimeter Data ◽  
Tide Gauges ◽  
Tidal Constituents ◽  
The Arctic Region

<p>The existence of seasonal variations in major tides has been recognized since decades. Where Corkan (1934) was the first to describe the seasonal perturbation of the M2 tide, many others have studied seasonal variations in the main tidal constituents since. However, most of these studies are based on sea level observations from tide gauges and are often restricted to coastal and shelf regions. Hence, observed seasonal variations are typically dominated by local processes and the large-scale patterns cannot be clearly distinguished. Moreover, most tide models still perceive tides as annually constant and seasonal variation in tides is ignored in the correction process of satellite altimetry. This results in reduced accuracy of obtained sea level anomalies. </p><p>To gain more insight in the large-scale seasonal variations in tides, we supplemented the clustered and sparsely distributed sea level observations from tide gauges by the wealth of data from satellite altimeters. Although altimeter-derived water levels are being widely used to obtain tidal constants, only few of these implementations consider seasonal variation in tides. For that reason, we have set out to explore the opportunities provided by altimeter data for deriving seasonal modulation of the main tidal constituents. Different methods were implemented and compared for the principal tidal constituents and a range of geographical domains, using data from a selection of satellite altimeters. Specific attention was paid to the Arctic region where seasonal variation in tides was expected to be significant as a result of the seasonal sea ice cycle, yet data availability is particularly limited. Our study demonstrates the potential of satellite altimetry for the quantification of seasonal modulation of tides and suggests the seasonal modulation to be considerable. Already for M2 we observed changes in tidal amplitude of the order of decimeters for the Arctic region, and centimeters for lower latitude regions.</p><p> </p><div>Corkan, R. H. (1934). An annual perturbation in the range of tide. <em>Proceedings of the Royal Society of London. Series A, Containing Papers of a Mathematical and Physical Character</em>, <em>144</em>(853), 537-559.</div>

scholarly journals Effect of Seasonal Variation on Clinical Outcome in Patients with Chronic Conditions: Analysis of the Commonwealth Scientific and Industrial Research Organization (CSIRO) National Telehealth Trial (Preprint)

2017 ◽  
Author(s):  
Ahmadreza Argha ◽  
Andrey Savkin ◽  
Siaw-Teng Liaw ◽  
Branko George Celler
Keyword(s):  
Seasonal Variation ◽  
Length Of Stay ◽  
Clinical Outcome ◽  
Seasonal Variations ◽  
Chronic Conditions ◽  
Hospital Admissions ◽  
Australian Capital Territory ◽  
Home Telemonitoring ◽  
The Impact ◽  
At Home

BACKGROUND Seasonal variation has an impact on the hospitalization rate of patients with a range of cardiovascular diseases, including myocardial infarction and angina. This paper presents findings on the influence of seasonal variation on the results of a recently completed national trial of home telemonitoring of patients with chronic conditions, carried out at five locations along the east coast of Australia. OBJECTIVE The aim is to evaluate the effect of the seasonal timing of hospital admission and length of stay on clinical outcome of a home telemonitoring trial involving patients (age: mean 72.2, SD 9.4 years) with chronic conditions (chronic obstructive pulmonary disease coronary artery disease, hypertensive diseases, congestive heart failure, diabetes, or asthma) and to explore methods of minimizing the influence of seasonal variations in the analysis of the effect of at-home telemonitoring on the number of hospital admissions and length of stay (LOS). METHODS Patients were selected from a hospital list of eligible patients living with a range of chronic conditions. Each test patient was case matched with at least one control patient. A total of 114 test patients and 173 control patients were available in this trial. However, of the 287 patients, we only considered patients who had one or more admissions in the years from 2010 to 2012. Three different groups were analyzed separately because of substantially different climates: (1) Queensland, (2) Australian Capital Territory and Victoria, and (3) Tasmania. Time series data were analyzed using linear regression for a period of 3 years before the intervention to obtain an average seasonal variation pattern. A novel method that can reduce the impact of seasonal variation on the rate of hospitalization and LOS was used in the analysis of the outcome variables of the at-home telemonitoring trial. RESULTS Test patients were monitored for a mean 481 (SD 77) days with 87% (53/61) of patients monitored for more than 12 months. Trends in seasonal variations were obtained from 3 years’ of hospitalization data before intervention for the Queensland, Tasmania, and Australian Capital Territory and Victoria subgroups, respectively. The maximum deviation from baseline trends for LOS was 101.7% (SD 42.2%), 60.6% (SD 36.4%), and 158.3% (SD 68.1%). However, by synchronizing outcomes to the start date of intervention, the impact of seasonal variations was minimized to a maximum of 9.5% (SD 7.7%), thus improving the accuracy of the clinical outcomes reported. CONCLUSIONS Seasonal variations have a significant effect on the rate of hospital admission and LOS in patients with chronic conditions. However, the impact of seasonal variation on clinical outcomes (rate of admissions, number of hospital admissions, and LOS) of at-home telemonitoring can be attenuated by synchronizing the analysis of outcomes to the commencement dates for the telemonitoring of vital signs. CLINICALTRIAL Australian New Zealand Clinical Trial Registry ACTRN12613000635763; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=364030&isReview=true (Archived by WebCite at http://www.webcitation.org/ 6xLPv9QDb)

scholarly journals Pedogenic carbonate sampling for Cu exploration on the Yorke Peninsula, South Australia

2018 ◽  
Vol 194 ◽  
pp. 239-256 ◽  
Author(s):  
Keryn Wolff ◽  
Caroline Tiddy ◽  
Dave Giles ◽  
Steve M. Hill
Keyword(s):  
South Australia ◽  
Pedogenic Carbonate ◽  
Yorke Peninsula

Difference of seasonal variation between glycated albumin and glycated haemoglobin

2018 ◽  
Vol 55 (5) ◽  
pp. 583-587 ◽  
Author(s):  
Karin Tanaka ◽  
Shu Meguro ◽  
Masami Tanaka ◽  
Junichiro Irie ◽  
Yoshifumi Saisho ◽  
...  
Keyword(s):  
Seasonal Variation ◽  
Plasma Glucose ◽  
Seasonal Variations ◽  
Glycated Albumin ◽  
Rank Correlation ◽  
Correlation Coefficients ◽  
Glycated Haemoglobin ◽  
Spearman Rank Correlation ◽  
Spearman Rank ◽  
Average Temperature

Background Glycated albumin reflects 2–3-week glycaemic controls, and in addition to glycated haemoglobin, it has been used as a glycaemic control indicator. We presumed that glycated albumin also has seasonal variations and is related to temperature, similar to glycated haemoglobin. Methods The subjects were diabetic outpatients from April 2007 to March 2013. This resulted in the enrolment of 2246 subjects and the collection of a total of 53,968 measurements. Mean glycated haemoglobin, glycated albumin, and plasma glucose were calculated for each month over six years. The associations of the measures with each other and the average temperature for each month in Tokyo were assessed using Spearman rank correlation coefficients. Results Plasma glucose was highest in January and lowest in May. Glycated haemoglobin was highest in March and lowest in September. Glycated albumin was highest in May and lowest in December. Glycated albumin tended to have a disjunction with plasma glucose in winter. Glycated haemoglobin had seasonal variation, but glycated albumin did not. Plasma glucose and glycated haemoglobin showed significant negative correlations with temperature (rs = −0.359, P < 0.001, rs = −0.449, P < 0.001, respectively), but glycated albumin did not. However, glycated albumin was inter-correlated with plasma glucose (rs = 0.396, P < 0.001) and glycated haemoglobin (rs = 0.685, P < 0.001), and glycated haemoglobin was inter-correlated with plasma glucose (rs = 0.465, P < 0.001). Conclusion Glycated albumin and glycated haemoglobin showed different seasonal variations from each other over the six-year study period. Thus, further studies to identify factors that contribute to glycated albumin are needed.

Seasonal variations of mode-1 M2 internal tides observed by satellite altimetry

2021 ◽  
Author(s):  
Zhongxiang Zhao
Keyword(s):  
Seasonal Variation ◽  
Seasonal Variations ◽  
Internal Tide ◽  
Spatial Filtering ◽  
Internal Tides ◽  
Mapping Technique ◽  
Phase Variable ◽  
Model Errors ◽  
Tropical Zone ◽  
Variable Amplitude

&lt;p&gt;The seasonal variations of M&lt;sub&gt;2&lt;/sub&gt; internal tides is investigated using 25 years of satellite altimetric sea surface height measurements from 1992--2017. The satellite data are divided into four seasonal subsets, from which four seasonal M&lt;sub&gt;2&lt;/sub&gt; internal tide models are constructed. This study employs a new mapping technique that combines along-track spatial filtering, harmonic analysis, plane wave analysis, and two-dimensional spatial filtering. The vector mean of the four seasonal models yields the seasonal-mean model, which is equivalent to the 25-year-coherent model constructed directly using all the data. The seasonal models have larger errors than the seasonal-mean model, because the seasonally-subsetted data sets are short. Two seasonally-variable models are derived: The first model is a step function of the four seasonal models (phase-variable, amplitude-variable); The second model is same as the first one but that the amplitude is from the seasonal-mean model (phase-variable, amplitude-invariable). All these models are evaluated using independent CryoSat-2 data. Each seasonal model reduces most variance in its own season and least variance in its opposite season. Based on globally-integrated variance reductions, the two seasonally-variable models reduce 13% and 23% more variance than the seasonal models, respectively. The seasonal-mean model can reduce 27% more variance, thanks to its small model errors. However, the seasonally-variable models are better than the seasonal-mean model in the tropical zone, where the seasonal signals are larger than model errors. The satellite results reveal that M&lt;sub&gt;2&lt;/sub&gt; internal tides are subject to seasonal variation in varying degrees and that the seasonal variation is a function of location. Large variations in amplitude and phase mainly occur in the tropical zone. The seasonal phase variations are mainly caused by the seasonal variations of ocean stratification and internal tide speed. Significant amplitude variations are usually associated with strong internal tides such as from the Luzon and Lombok Straits, and in the Amazon River plume, the western Pacific and the Arabian Sea. At higher latitudes such as the North Pacific and North Atlantic Oceans, the seasonal variations are weak but detectable. The seasonally-variable models can partly account for the seasonal variations of internal tides, in particular, in the tropical zone. &amp;#160;A major challenge is the large model errors, which will be further reduced with the accumulation of new altimeter missions and data (e.g., SWOT).&lt;/p&gt;

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