991 resultados para Seasonal migration


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OBJECTIVE To monitor the seasonal body composition alterations in 18 lightweight rowers (six females, 12 males) across a rowing season incorporating preseason, early competition, competition, and postseason. METHODS Subject age was 23.1 (SD 4.5) years, height 170.8 (5.6) cm (female, 23.5 (3.5) years, 180.5 (2.7) cm (male). Body weight, fat mass, and fat-free mass (FFM) were assessed using dual energy x ray absorptiometry (DXA-L Lunar) and skinfold techniques. Weight control techniques were documented before major regattas by a questionnaire. RESULTS Female body weight was reduced from 61.3 (2.9) to 57.0 (1.1) kg (5.9%), while male body weight was reduced from 75.6 (3.1) to 69.8 (1.6) kg (7.8%) preseason to competition season respectively. These body weight reductions were mirrored by a significant reduction in fat mass as indicated by the sum of skinfolds [female seven sites: 80.9 (8.1) to 68.2 (11.8) mm; male eight sites: 54.2 (8.7) to 41.8 (4.8) mm], percentage body fat [female 22.1 (1.0) to 19.7 (2.4)%; male 10.0 (0.9) to 7.8 (0.8)%], and total fat [female 12.5 (5.2) to 10.9 (1.4) kg; male 7.3 (1.9) to 5.6 (1.8) kg] (DXA). In contrast, no changes were observed in FFM despite a season of intensive rowing training. Seasonal body weight control was achieved through reduced total energy and dietary fat intakes. Acute body weight reductions were achieved by exercise in 73.3% of participants, food restriction in 71.4%, and fluid restrictions in 62.9%. CONCLUSIONS Seasonal body weight alterations in lightweight rowers are in response to a significant reduction in fat mass. However, the weight restrictions appear to be limiting an increase in FFM which could be beneficial to rowing performance.

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To quantify the role of Johnson grass, Sorghum halepense, in the population dynamics of the sorghum midge, Stenodiplosis sorghicola, patterns of flowering of Johnson grass and infestation by sorghum midge were studied in two different climatic environments in the Lockyer Valley and on the Darling Downs in south-eastern Queensland for 3 years. Parasitism levels of S. sorghicola were also recorded. In the Lockyer Valley, Johnson grass panicles were produced throughout the year but on the Darling Downs none were produced between June and September. In both areas, most panicle production occurred between November and March and infestation by S. sorghicola was the greatest during this period. The parasitism levels were between 20% and 50%. After emergence from winter diapause, one to two generations of S. sorghicola developed on S. halepense before commercial grain sorghum crops were available for infestation. Parasitoids recorded were: Aprostocetus diplosidis, Eupelmus australiensis and two species of Tetrastichus. Relationships between sorghum midge population growth rate and various environmental and population variables were investigated. Population size had a significant negative effect (P < 0.0001) on population growth rate. Mortality due to parasitism showed a significant positive density response (P < 0.0001). Temperature, rainfall, open pan evaporation, degree-days and host availability showed no significant effect on population growth rate. Given the phenology of sorghum production in south-eastern Queensland, Johnson grass provides an important bridging host, sustaining one to two generations of sorghum midge. Critical studies relating population change and build-up in sorghum to sorghum midge populations in Johnson grass are yet to be performed.

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Cereal grain is one of the main export commodities of Australian agriculture. Over the past decade, crop yield forecasts for wheat and sorghum have shown appreciable utility for industry planning at shire, state, and national scales. There is now an increasing drive from industry for more accurate and cost-effective crop production forecasts. In order to generate production estimates, accurate crop area estimates are needed by the end of the cropping season. Multivariate methods for analysing remotely sensed Enhanced Vegetation Index (EVI) from 16-day Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery within the cropping period (i.e. April-November) were investigated to estimate crop area for wheat, barley, chickpea, and total winter cropped area for a case study region in NE Australia. Each pixel classification method was trained on ground truth data collected from the study region. Three approaches to pixel classification were examined: (i) cluster analysis of trajectories of EVI values from consecutive multi-date imagery during the crop growth period; (ii) harmonic analysis of the time series (HANTS) of the EVI values; and (iii) principal component analysis (PCA) of the time series of EVI values. Images classified using these three approaches were compared with each other, and with a classification based on the single MODIS image taken at peak EVI. Imagery for the 2003 and 2004 seasons was used to assess the ability of the methods to determine wheat, barley, chickpea, and total cropped area estimates. The accuracy at pixel scale was determined by the percent correct classification metric by contrasting all pixel scale samples with independent pixel observations. At a shire level, aggregated total crop area estimates were compared with surveyed estimates. All multi-temporal methods showed significant overall capability to estimate total winter crop area. There was high accuracy at pixel scale (>98% correct classification) for identifying overall winter cropping. However, discrimination among crops was less accurate. Although the use of single-date EVI data produced high accuracy for estimates of wheat area at shire scale, the result contradicted the poor pixel-scale accuracy associated with this approach, due to fortuitous compensating errors. Further studies are needed to extrapolate the multi-temporal approaches to other geographical areas and to improve the lead time for deriving cropped-area estimates before harvest.

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The Wet Tropics bioregion of north Queensland has been identified as an area of global significance. The world-heritage-listed rainforests have been invaded by feral pigs (Sus scrofa) that are perceived to cause substantial environmental damage. A community perception exists of an annual altitudinal migration of the feral-pig population. The present study describes the movements of 29 feral pigs in relation to altitudinal migration (highland, transitional and lowland areas). Feral pigs were sedentary and stayed within their home range throughout a 4-year study period. No altitudinal migration was detected; pigs moved no more than a mean distance of 1.0 km from the centre of their calculated home ranges. There was no significant difference between the mean (+/- 95% confidence interval) aggregate home ranges for males (8.7 +/- 4.3 km², n = 15) and females (7.2 +/- 1.8 km², n = 14). No difference in home range was detected among the three altitudinal areas: 7.2 +/- 2.4 km² for highland, 6.2 +/- 3.9 km² for transitional and 9.9 +/- 5.3 km² for lowland areas. The aggregate mean home range for all pigs in the present study was 8.0 +/- 2.4 km². The study also assessed the influence seasons had on the home range of eight feral pigs on the rainforest boundary; home ranges did not significantly vary in size between the tropical wet and dry seasons, although the mean home range in the dry season (7.7 +/- 6.9 km²) was more than twice the home range in the wet season (2.9 +/- 0.8 km²). Heavier pigs tended to have larger home ranges. The results of the present study suggest that feral pigs are sedentary throughout the year so broad-scale control techniques need to be applied over sufficient areas to encompass individual home ranges. Control strategies need a coordinated approach if a long-term reduction in the pig population is to be achieved.

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The prospect of widespread displacement in the Pacific as a result of climate change is becoming increasingly likely and it is possible that many will eventually need to relocate to other countries. Regional migration strategies not only offer the potential to minimise the harms of relocation, while acknowledging existing relationships of friendship and regional cooperation. This article examines the use of the language of ‘neighbourliness’ in Australia’s regional climate change strategies and argues that, while it expresses friendship, such language can also be employed to avoid the creation of stronger obligations. The article considers the international doctrine of good neighbourliness and concludes that, while international legal obligations may not yet exist, Australia should nonetheless begin planning for regional migration within the Pacific to allow people to migrate with dignity.

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Bemisia tabaci, biotype B, commonly known as the silverleaf whitefly (SLW) is an alien species that invaded Australia in the mid-90s. This paper reports on the invasion ecology of SLW and the factors that are likely to have contributed to the first outbreak of this major pest in an Australian cotton cropping system, population dynamics of SLW within whitefly-susceptible crop (cotton and cucurbit) and non-crop vegetation (sowthistle, Sonchus spp.) components of the cropping system were investigated over four consecutive growing seasons (September-June) 2001/02-2004/05 in the Emerald Irrigation Area (EIA) of Queensland, Australia. Based on fixed geo-referenced sampling sites, variation in spatial and temporal abundance of SLW within each system component was quantified to provide baseline data for the development of ecologically sustainable pest management strategies. Parasitism of large (3rd and 4th instars) SLW nymphs by native aphelinid wasps was quantified to determine the potential for natural control of SLW populations. Following the initial outbreak in 2001/02, SLW abundance declined and stabilised over the next three seasons. The population dynamics of SLW is characterised by inter-seasonal population cycling between the non-crop (weed) and cotton components of the EIA cropping system. Cotton was the largest sink for and source of SLW during the study period. Over-wintering populations dispersed from weed host plant sources to cotton in spring followed by a reverse dispersal in late summer and autumn to broad-leaved crops and weeds. A basic spatial source-sink analysis showed that SLW adult and nymph densities were higher in cotton fields that were closer to over-wintering weed sources throughout spring than in fields that were further away. Cucurbit fields were not significant sources of SLW and did not appear to contribute significantly to the regional population dynamics of the pest. Substantial parasitism of nymphal stages throughout the study period indicates that native parasitoid species and other natural enemies are important sources of SLW mortality in Australian cotton production systems. Weather conditions and use of broad-spectrum insecticides for pest control are implicated in the initial outbreak and on-going pest status of SLW in the region.

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The variation in liveweight gain in grazing beef cattle as influenced by pasture type, season and year effects has important economic implications for mixed crop-livestock systems and the ability to better predict such variation would benefit beef producers by providing a guide for decision making. To identify key determinants of liveweight change of Brahman-cross steers grazing subtropical pastures, measurements of pasture quality and quantity, and diet quality in parallel with liveweight were made over two consecutive grazing seasons (48 and 46 weeks, respectively), on mixed Clitoria ternatea/grass, Stylosanthes seabrana/grass and grass swards (grass being a mixture of Bothriochloa insculpta cv. Bisset, Dichanthium sericeum and Panicum maximum var. trichoglume cv. Petrie). Steers grazing the legume-based pastures had the highest growth rate and gained between 64 and 142 kg more than those grazing the grass pastures in under 12 months. Using an exponential model, green leaf mass, green leaf %, adjusted green leaf % (adjusted for inedible woody legume stems), faecal near infrared reflectance spectroscopy predictions of diet crude protein and diet dry matter digestibility, accounted for 77, 74, 80, 63 and 60%, respectively, of the variation in daily weight gain when data were pooled across pasture types and grazing seasons. The standard error of the regressions indicated that 95% prediction intervals were large (+/- 0.42-0.64 kg/head.day) suggesting that derived regression relationships have limited practical application for accurately estimating growth rate. In this study, animal factors, especially compensatory growth effects, appeared to have a major influence on growth rate in relation to pasture and diet attributes. It was concluded that predictions of growth rate based only on pasture or diet attributes are unlikely to be accurate or reliable. Nevertheless, key pasture attributes such as green leaf mass and green leaf% provide a robust indication of what proportion of the potential growth rate of the grazing animals can be achieved.

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A highly polymorphic genetic locus of Stout Whiting was examined for evidence of geographical subdivision amongst samples collected from three locales in southern Queensland waters. Statistical indicators of subdivision were not significantly different from zero, suggesting that it is unlikely that the Stout Whiting resource in southern Queensland is genetically subdivided into separate stocks. It is recommended that the full-scale genetic program not proceed and that the resource be managed as a single stock.

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Coastal seagrass habitats in tropical and subtropical regions support aggregations of resident green turtles (Chelonia mydas) from several genetically distinct breeding populations. Migration of individuals to their respective dispersed breeding sites provides a complex pattern of migratory connectivity among nesting and feeding habitats of this species. An understanding of this pattern is important in regions where the persistence of populations is under threat from anthropogenic impacts. The present study uses mitochondrial DNA and mixed-stock analyses to assess the connectivity among seven feeding grounds across the north Australian coast and adjacent areas and 17 genetically distinct breeding populations from the Indo-Pacific region. It was hypothesised that large and geographically proximate breeding populations would dominate at nearby feeding grounds. As expected, each sampled feeding area appears to support multiple breeding populations, with two aggregations dominated by a local breeding population. Geographic distance between breeding and feeding habitat strongly influenced whether a breeding population contributed to a feeding ground (wi = 0.654); however, neither distance nor size of a breeding population was a good predictor of the extent of their contribution. The differential proportional contributions suggest the impact of anthropogenic mortality at feeding grounds should be assessed on a case-by-case basis.

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The aim of this study was to measure seasonal variation in mood and behaviour. The dual vulnerability and latitude effect hypothesis, the risk of increased appetite, weight and other seasonal symptoms to develop metabolic syndrome, and perception of low illumination in quality of life and mental well-being were assessed. These variations are prevalent in persons who live in high latitudes and need balancing of metabolic processes to adapt to environmental changes due to seasons. A randomized sample of 8028 adults aged 30 and over (55% women) participated in an epidemiological health examination study, The Health 2000, applying the probability proportional to population size method for a range of socio-demographic characteristics. They were present in a face-to-face interview at home and health status examination. The questionnaires included the modified versions of the Seasonal Pattern Assessment Questionnaire (SPAQ) and Beck Depression Inventory (BDI), the Health Related Quality of Life (HRQoL) instrument 15D, and the General Health Questionnaire (GHQ). The structured and computerized Munich Composite International Diagnostic Interview (M-CIDI) as part of the interview was used to assess diagnoses of mental disorders, and, the National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATPIII) criteria were assessed using all the available information to detect metabolic syndrome. A key finding was that 85% of this nationwide representative sample had seasonal variation in mood and behaviour. Approximately 9% of the study population presented combined seasonal and depressive symptoms with a significant association between their scores, and 2.6% had symptoms that corresponded to Seasonal Affective Disorder (SAD) in severity. Seasonal variations in weight and appetite are two important components that increase the risk of metabolic syndrome. Other factors such as waist circumference and major depressive disorder contributed to the metabolic syndrome as well. Persons reported of having seasonal symptoms were associated with a poorer quality of life and compromised mental well-being, especially if indoors illumination at home and/or at work was experienced as being low. Seasonal and circadian misalignments are suggested to associate with metabolic disorders, and could be remarked if individuals perceive low illumination levels at home and/or at work that affect the health-related quality of life and mental well-being. Keywords: depression, health-related quality of life, illumination, latitude, mental well-being, metabolic syndrome, seasonal variation, winter.

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A small fraction of the energy absorbed in the light reactions of photosynthesis is re-emitted as chlorophyll-a fluorescence. Chlorophyll-a fluorescence and photochemistry compete for excitation energy in photosystem II (PSII). Therefore, changes in the photochemical capacity can be detected through analysis of chlorophyll fluorescence. Chlorophyll fluorescence techniques have been widely used to follow the diurnal (fast), and the seasonal (slow) acclimation in the energy partitioning between photochemical and non-photochemical processes in PSII. Energy partitioning in PSII estimated through chlorophyll fluorescence can be used as a proxy of the plant physiological status, and measured at different spatial and temporal scales. However, a number of technical and theoretical limitations still limit the use of chlorophyll fluorescence data for the study of the acclimation of PSII. The aim of this Thesis was to study the diurnal and seasonal acclimation of PSII in field conditions through the development and testing of new chlorophyll fluorescence-based tools, overcoming these limitations. A new model capable of following the fast acclimation of PSII to rapid fluctuations in light intensity was developed. The model was used to study the rapid acclimation in the electron transport rate under fluctuating light. Additionally, new chlorophyll fluorescence parameters were developed for estimating the seasonal acclimation in the sustained rate constant of thermal energy dissipation and photochemistry. The parameters were used to quantitatively evaluate the effect of light and temperature on the seasonal acclimation of PSII. The results indicated that light environment not only affected the degree but also the kinetics of response of the acclimation to temperature, which was attributed to differences in the structural organization of PSII during seasonal acclimation. Furthermore, zeaxanthin-facilitated thermal dissipation appeared to be the main mechanisms modulating the fraction of absorbed energy being dissipated thermally during winter in field Scots pine. Finally, the integration between diurnal and seasonal acclimation mechanisms was studied using a recently developed instrument MONI-PAM (Walz GmbH, Germany) capable of continuously monitoring the energy partitioning in PSII.

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Fourier Transform (FT)-near infra-red spectroscopy (NIRS) was investigated as a non-invasive technique for estimating percentage (%) dry matter of whole intact 'Hass' avocado fruit. Partial least squares (PLS) calibration models were developed from the diffuse reflectance spectra to predict % dry matter, taking into account effects of seasonal variation. It is found that seasonal variability has a significant effect on model predictive performance for dry matter in avocados. The robustness of the calibration model, which in general limits the application for the technique, was found to increase across years (seasons) when more seasonal variability was included in the calibration set. The R-v(2) and RMSEP for the single season prediction models predicting on an independent season ranged from 0.09 to 0.61 and 2.63 to 5.00, respectively, while for the two season models predicting on the third independent season, they ranged from 0.34 to 0.79 and 2.18 to 2.50, respectively. The bias for single season models predicting an independent season was as high as 4.429 but <= 1.417 for the two season combined models. The calibration model encompassing fruit from three consecutive years yielded predictive statistics of R-v(2) = 0.89, RMSEP = 1.43% dry matter with a bias of -0.021 in the range 16.1-39.7% dry matter for the validation population encompassing independent fruit from the three consecutive years. Relevant spectral information for all calibration models was obtained primarily from oil, carbohydrate and water absorbance bands clustered in the 890-980, 1005-1050, 1330-1380 and 1700-1790 nm regions. These results indicate the potential of FT-NIRS, in diffuse reflectance mode, to non-invasively predict the % dry matter of whole 'Hass' avocado fruit and the importance of the development of a calibration model that incorporates seasonal variation. Crown Copyright (c) 2012 Published by Elsevier B.V. All rights reserved.