Daily manifestations of career adaptability: Relationships with job and career outcomes

Most research on career adaptability has examined the construct as an individual differences variable and neglected that it may vary within an individual over a short period of time. In two daily diary studies, the author investigated the relationships of career adaptability and its four dimensions (concern, control, curiosity, and confidence) to their daily manifestations as well as daily job and career outcomes. Both Study 1 (N = 53) and Study 2 (N = 234) demonstrated substantial within-person variability in employees' behavioral expressions of career adaptability across five work days. Results further showed that daily career adaptability and daily confidence positively predicted daily task and career performance, as well as daily job and career satisfaction. Daily control positively predicted daily task performance, as well as daily job and career satisfaction. Daily concern positively predicted daily career performance and satisfaction, and daily curiosity positively predicted daily career satisfaction.

Variability in exposure to ambient ultrafine particles in urban schools: Comparative assessment between Australia and Spain

Ambient ultrafine particle number concentrations (PNC) have inhomogeneous spatio-temporal distributions and depend on a number of different urban factors, including background conditions and distant sources. This paper quantitatively compares exposure to ambient ultrafine particles at urban schools in two cities in developed countries, with high insolation climatic conditions, namely Brisbane (Australia) and Barcelona (Spain). The analysis used comprehensive indoor and outdoor air quality measurements at 25 schools in Brisbane and 39 schools in Barcelona. PNC modes were analysed with respect to ambient temperature, land use and urban characteristics, combined with the measured elemental carbon concentrations, NOx (Brisbane) and NO2 (Barcelona). The trends and modes of the quantified weekday average daily cycles of ambient PNC exhibited significant differences between the two cities. PNC increases were observed during traffic rush hours in both cases. However, the mid-day peak was dominant in Brisbane schools and had the highest contribution to total PNC for both indoors and outdoors. In Barcelona, the contribution from traffic was highest for ambient PNC, while the mid-day peak had a slightly higher contribution for indoor concentrations. Analysis of the relationships between PNC and land use characteristics in Barcelona schools showed a moderate correlation with the percentage of road network area and an anti-correlation with the percentage of green area. No statistically significant correlations were found for Brisbane. Overall, despite many similarities between the two cities, school-based exposure patterns were different. The main source of ambient PNC at schools was shown to be traffic in Barcelona and mid-day new particle formation in Brisbane. The mid-day PNC peak in Brisbane could have been driven by the combined effect of background and meteorological conditions, as well as other local/distant sources. The results have implications for urban development, especially in terms of air quality mitigation and management at schools.

Foraging Behaviour and Landscape Utilisation by the Endangered Golden-Crowned Flying Fox (Acerodon jubatus), The Philippines

Species of Old World fruit-bats (family Pteropodidae) have been identified as the natural hosts of a number of novel and highly pathogenic viruses threatening livestock and human health. We used GPS data loggers to record the nocturnal foraging movements of Acerodon jubatus, the Golden-crowned flying fox in the Philippines to better understand the landscape utilisation of this iconic species, with the dual objectives of pre-empting disease emergence and supporting conservation management. Data loggers were deployed on eight of 54 A. jubatus (two males and six females) captured near Subic Bay on the Philippine island of Luzon between 22 November and 2 December 2010. Bodyweight ranged from 730 g to 1002 g, translating to a weight burden of 3–4% of bodyweight. Six of the eight loggers yielded useful data over 2–10 days, showing variability in the nature and range of individual bat movements. The majority of foraging locations were in closed forest and most were remote from evident human activity. Forty-six discrete foraging locations and five previously unrecorded roost locations were identified. Our findings indicate that foraging is not a random event, with the majority of bats exhibiting repetitious foraging movements night-to-night, that apparently intact forest provides the primary foraging resource, and that known roost locations substantially underestimate the true number (and location) of roosts. Our initial findings support policy and decision-making across perspectives including landscape management, species conservation, and potentially disease emergence.

Large-chamber methane and nitrous oxide measurements are comparable to the backward Lagrangian stochastic method

Measurement of individual emission sources (e.g., animals or pen manure) within intensive livestock enterprises is necessary to test emission calculation protocols and to identify targets for decreased emissions. In this study, a vented, fabric-covered large chamber (4.5 × 4.5 m, 1.5 m high; encompassing greater spatial variability than a smaller chamber) in combination with on-line analysis (nitrous oxide [N2O] and methane [CH4] via Fourier Transform Infrared Spectroscopy; 1 analysis min-1) was tested as a means to isolate and measure emissions from beef feedlot pen manure sources. An exponential model relating chamber concentrations to ambient gas concentrations, air exchange (e.g., due to poor sealing with the surface; model linear when ≈ 0 m3 s-1), and chamber dimensions allowed data to be fitted with high confidence. Alternating manure source emission measurements using the large-chamber and the backward Lagrangian stochastic (bLS) technique (5-mo period; bLS validated via tracer gas release, recovery 94-104%) produced comparable N2O and CH4 emission values (no significant difference at P < 0.05). Greater precision of individual measurements was achieved via the large chamber than for the bLS (mean ± standard error of variance components: bLS half-hour measurements, 99.5 ± 325 mg CH4 s-1 and 9.26 ± 20.6 mg N2O s-1; large-chamber measurements, 99.6 ± 64.2 mg CH4 s-1 and 8.18 ± 0.3 mg N2O s-1). The large-chamber design is suitable for measurement of emissions from manure on pen surfaces, isolating these emissions from surrounding emission sources, including enteric emissions. © © American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.

Sustainable grazing management for temporal and spatial variability in north Australian rangelands – a synthesis of the latest evidence and recommendations

Rainfall variability is a major challenge to sustainable grazing management in northern Australia, with management often complicated further by large, spatially-heterogeneous paddocks. This paper presents the latest grazing research and associated bio-economic modelling from northern Australia and assesses the extent to which current recommendations to manage for these issues are supported. Overall, stocking around the safe long-term carrying capacity will maintain land condition and maximise long-term profitability. However, stocking rates should be varied in a risk-averse manner as pasture availability varies between years. Periodic wet-season spelling is also essential to maintain pasture condition and allow recovery of overgrazed areas. Uneven grazing distributions can be partially managed through fencing, providing additional water-points and in some cases patch-burning, although the economics of infrastructure development are extremely context-dependent. Overall, complex multi-paddock grazing systems do not appear justified in northern Australia. Provided the key management principles outlined above are applied in an active, adaptive manner, acceptable economic and environmental outcomes will be achieved irrespective of the grazing system applied.

Investigation of the effects of extracellular osmotic pressure on morphology and mechanical 1 properties of individual chondrocyte

It has been demonstrated that most cells of the body respond to osmotic pressure in a systematic manner. The disruption of the collagen network in the early stages of osteoarthritis causes an increase in water content of cartilage which leads to a reduction of pericellular osmolality in chondrocytes distributed within the extracellular environment. It is therefore arguable that an insight into the mechanical properties of chondrocytes under varying osmotic pressure would provide a better understanding of chondrocyte mechanotransduction and potentially contribute to knowledge on cartilage degeneration. In this present study, the chondrocyte cells were exposed to solutions with different osmolality. Changes in their dimensions and mechanical properties were measured over time. Atomic Force Microscopy (AFM) was used to apply load at various strain-rates and the force-time curves were logged. The thin-layer elastic model was used to extract the elastic stiffness of chondrocytes at different strain-rates and at different solution osmolality. In addition, the porohyperelastic (PHE) model was used to investigate the strain-rate dependent responses under the loading and osmotic pressure conditions. The results revealed that the hypo-osmotic external environment increased chondrocyte dimensions and reduced Young’s modulus of the cells at all strain-rates tested. In contrast, the hyper-osmotic external environment reduced dimensions and increased Young’s modulus. Moreover, by using the PHE model coupled with inverse FEA simulation, we established that the hydraulic permeability of chondrocytes increased with decreasing extracellular osmolality which is consistent with previous work in the literature. This could be due to a higher intracellular fluid volume fraction with lower osmolality.

Stock assessment of the Queensland east coast common coral trout (Plectropomus leopardus) fishery

Common coral trout Plectropomus leopardus is an iconic fish of the Great Barrier Reef (GBR) and is the most important fish for the commercial fishery there. Most of the catch is exported live to Asia. This stock assessment was undertaken in response to falls in catch sizes and catch rates in recent years, in order to gauge the status of the stock. It is the first stock assessment ever conducted of coral trout on the GBR, and brings together a multitude of different data sources for the first time. The GBR is very large and was divided into a regional structure based on the Bioregions defined by expert committees appointed by the Great Barrier Reef Marine Park Authority (GBRMPA) as part of the 2004 rezoning of the GBR. The regional structure consists of six Regions, from the Far Northern Region in the north to the Swains and Capricorn–Bunker Regions in the south. Regions also closely follow the boundaries between Bioregions. Two of the northern Regions are split into Subregions on the basis of potential changes in fishing intensity between the Subregions; there are nine Subregions altogether, which include four Regions that are not split. Bioregions are split into Subbioregions along the Subregion boundaries. Finally, each Subbioregion is split into a “blue” population which is open to fishing and a “green” population which is closed to fishing. The fishery is unusual in that catch rates as an indicator of abundance of coral trout are heavily influenced by tropical cyclones. After a major cyclone, catch rates fall for two to three years, and rebound after that. This effect is well correlated with the times of occurrence of cyclones, and usually occurs in the same month that the cyclone strikes. However, statistical analyses correlating catch rates with cyclone wind energy did not provide significantly different catch rate trends. Alternative indicators of cyclone strength may explain more of the catch rate decline, and future work should investigate this. Another feature of catch rates is the phenomenon of social learning in coral trout populations, whereby when a population of coral trout is fished, individuals quickly learn not to take bait. Then the catch rate falls sharply even when the population size is still high. The social learning may take place by fish directly observing their fellows being hooked, or perhaps heeding a chemo-sensory cue emitted by fish that are hooked. As part of the assessment, analysis of data from replenishment closures of Boult Reef in the Capricorn–Bunker Region (closed 1983–86) and Bramble Reef in the Townsville Subregion (closed 1992–95) estimated a strong social learning effect. A major data source for the stock assessment was the large collection of underwater visual survey (UVS) data collected by divers who counted the coral trout that they sighted. This allowed estimation of the density of coral trout in the different Bioregions (expressed as a number of fish per hectare). Combined with mapping data of all the 3000 or so reefs making up the GBR, the UVS results provided direct estimates of the population size in each Subbioregion. A regional population dynamic model was developed to account for the intricacies of coral trout population dynamics and catch rates. Because the statistical analysis of catch rates did not attribute much of the decline to tropical cyclones, (and thereby implied “real” declines in biomass), and because in contrast the UVS data indicate relatively stable population sizes, model outputs were unduly influenced by the unlikely hypothesis that falling catch rates are real. The alternative hypothesis that UVS data are closer to the mark and declining catch rates are an artefact of spurious (e.g., cyclone impact) effects is much more probable. Judging by the population size estimates provided by the UVS data, there is no biological problem with the status of coral trout stocks. The estimate of the total number of Plectropomus leopardus on blue zones on the GBR in the mid-1980s (the time of the major UVS series) was 5.34 million legal-sized fish, or about 8400 t exploitable biomass, with an 2 additional 3350 t in green zones (using the current zoning which was introduced on 1 July 2004). For the offshore regions favoured by commercial fishers, the figure was about 4.90 million legal-sized fish in blue zones, or about 7700 t exploitable biomass. There is, however, an economic problem, as indicated by relatively low catch rates and anecdotal information provided by commercial fishers. The costs of fishing the GBR by hook and line (the only method compatible with the GBR’s high conservation status) are high, and commercial fishers are unable to operate profitably when catch rates are depressed (e.g., from a tropical cyclone). The economic problem is compounded by the effect of social learning in coral trout, whereby catch rates fall rapidly if fishers keep returning to the same fishing locations. In response, commercial fishers tend to spread out over the GBR, including the Far Northern and Swains Regions which are far from port and incur higher travel costs. The economic problem provides some logic to a reduction in the TACC. Such a reduction during good times, such as when the fishery is rebounding after a major tropical cyclone, could provide a net benefit to the fishery, as it would provide a margin of stock safety and make the fishery more economically robust by providing higher catch rates during subsequent periods of depressed catches. During hard times when catch rates are low (e.g., shortly after a major tropical cyclone), a change to the TACC would have little effect as even a reduced TACC would not come close to being filled. Quota adjustments based on catch rates should take account of long-term trends in order to mitigate variability and cyclone effects in data.

Spatial and temporal variability in midge (Nematocera) assemblages in shallow Finnish lakes (60−70 °N) : community-based modelling of past environmental change

Multi- and intralake datasets of fossil midge assemblages in surface sediments of small shallow lakes in Finland were studied to determine the most important environmental factors explaining trends in midge distribution and abundance. The aim was to develop palaeoenvironmental calibration models for the most important environmental variables for the purpose of reconstructing past environmental conditions. The developed models were applied to three high-resolution fossil midge stratigraphies from southern and eastern Finland to interpret environmental variability over the past 2000 years, with special focus on the Medieval Climate Anomaly (MCA), the Little Ice Age (LIA) and recent anthropogenic changes. The midge-based results were compared with physical properties of the sediment, historical evidence and environmental reconstructions based on diatoms (Bacillariophyta), cladocerans (Crustacea: Cladocera) and tree rings. The results showed that the most important environmental factor controlling midge distribution and abundance along a latitudinal gradient in Finland was the mean July air temperature (TJul). However, when the dataset was environmentally screened to include only pristine lakes, water depth at the sampling site became more important. Furthermore, when the dataset was geographically scaled to southern Finland, hypolimnetic oxygen conditions became the dominant environmental factor. The results from an intralake dataset from eastern Finland showed that the most important environmental factors controlling midge distribution within a lake basin were river contribution, water depth and submerged vegetation patterns. In addition, the results of the intralake dataset showed that the fossil midge assemblages represent fauna that lived in close proximity to the sampling sites, thus enabling the exploration of within-lake gradients in midge assemblages. Importantly, this within-lake heterogeneity in midge assemblages may have effects on midge-based temperature estimations, because samples taken from the deepest point of a lake basin may infer considerably colder temperatures than expected, as shown by the present test results. Therefore, it is suggested here that the samples in fossil midge studies involving shallow boreal lakes should be taken from the sublittoral, where the assemblages are most representative of the whole lake fauna. Transfer functions between midge assemblages and the environmental forcing factors that were significantly related with the assemblages, including mean air TJul, water depth, hypolimnetic oxygen, stream flow and distance to littoral vegetation, were developed using weighted averaging (WA) and weighted averaging-partial least squares (WA-PLS) techniques, which outperformed all the other tested numerical approaches. Application of the models in downcore studies showed mostly consistent trends. Based on the present results, which agreed with previous studies and historical evidence, the Medieval Climate Anomaly between ca. 800 and 1300 AD in eastern Finland was characterized by warm temperature conditions and dry summers, but probably humid winters. The Little Ice Age (LIA) prevailed in southern Finland from ca. 1550 to 1850 AD, with the coldest conditions occurring at ca. 1700 AD, whereas in eastern Finland the cold conditions prevailed over a longer time period, from ca. 1300 until 1900 AD. The recent climatic warming was clearly represented in all of the temperature reconstructions. In the terms of long-term climatology, the present results provide support for the concept that the North Atlantic Oscillation (NAO) index has a positive correlation with winter precipitation and annual temperature and a negative correlation with summer precipitation in eastern Finland. In general, the results indicate a relatively warm climate with dry summers but snowy winters during the MCA and a cool climate with rainy summers and dry winters during the LIA. The results of the present reconstructions and the forthcoming applications of the models can be used in assessments of long-term environmental dynamics to refine the understanding of past environmental reference conditions and natural variability required by environmental scientists, ecologists and policy makers to make decisions concerning the presently occurring global, regional and local changes. The developed midge-based models for temperature, hypolimnetic oxygen, water depth, littoral vegetation shift and stream flow, presented in this thesis, are open for scientific use on request.

Boosting the productivity and profitability of northern Australian beef enterprises: Exploring innovation options using simulation modelling and systems analysis

The financial health of beef cattle enterprises in northern Australia has declined markedly over the last decade due to an escalation in production and marketing costs and a real decline in beef prices. Historically, gains in animal productivity have offset the effect of declining terms of trade on farm incomes. This raises the question of whether future productivity improvements can remain a key path for lifting enterprise profitability sufficient to ensure that the industry remains economically viable over the longer term. The key objective of this study was to assess the production and financial implications for north Australian beef enterprises of a range of technology interventions (development scenarios), including genetic gain in cattle, nutrient supplementation, and alteration of the feed base through introduced pastures and forage crops, across a variety of natural environments. To achieve this objective a beef systems model was developed that is capable of simulating livestock production at the enterprise level, including reproduction, growth and mortality, based on energy and protein supply from natural C4 pastures that are subject to high inter-annual climate variability. Comparisons between simulation outputs and enterprise performance data in three case study regions suggested that the simulation model (the Northern Australia Beef Systems Analyser) can adequately represent the performance beef cattle enterprises in northern Australia. Testing of a range of development scenarios suggested that the application of individual technologies can substantially lift productivity and profitability, especially where the entire feedbase was altered through legume augmentation. The simultaneous implementation of multiple technologies that provide benefits to different aspects of animal productivity resulted in the greatest increases in cattle productivity and enterprise profitability, with projected weaning rates increasing by 25%, liveweight gain by 40% and net profit by 150% above current baseline levels, although gains of this magnitude might not necessarily be realised in practice. While there were slight increases in total methane output from these development scenarios, the methane emissions per kg of beef produced were reduced by 20% in scenarios with higher productivity gain. Combinations of technologies or innovative practices applied in a systematic and integrated fashion thus offer scope for providing the productivity and profitability gains necessary to maintain viable beef enterprises in northern Australia into the future.

Exploring the Potential Impacts of Climate Variability on Spring Wheat Yield with the APSIM Decision Support Tool

Assessing the impacts of climate variability on agricultural productivity at regional, national or global scale is essential for defining adaptation and mitigation strategies. We explore in this study the potential changes in spring wheat yields at Swift Current and Melfort, Canada, for different sowing windows under projected climate scenarios (i.e., the representative concentration pathways, RCP4.5 and RCP8.5). First, the APSIM model was calibrated and evaluated at the study sites using data from long term experimental field plots. Then, the impacts of change in sowing dates on final yield were assessed over the 2030-2099 period with a 1990-2009 baseline period of observed yield data, assuming that other crop management practices remained unchanged. Results showed that the performance of APSIM was quite satisfactory with an index of agreement of 0.80, R2 of 0.54, and mean absolute error (MAE) and root mean square error (RMSE) of 529 kg/ha and 1023 kg/ha, respectively (MAE = 476 kg/ha and RMSE = 684 kg/ha in calibration phase). Under the projected climate conditions, a general trend in yield loss was observed regardless of the sowing window, with a range from -24 to -94 depending on the site and the RCP, and noticeable losses during the 2060s and beyond (increasing CO2 effects being excluded). Smallest yield losses obtained through earlier possible sowing date (i.e., mid-April) under the projected future climate suggested that this option might be explored for mitigating possible adverse impacts of climate variability. Our findings could therefore serve as a basis for using APSIM as a decision support tool for adaptation/mitigation options under potential climate variability within Western Canada.

Estimating daily methane production in individual cattle with irregular feed intake patterns from short-term methane emission measurements

Spot measurements of methane emission rate (n = 18 700) by 24 Angus steers fed mixed rations from GrowSafe feeders were made over 3- to 6-min periods by a GreenFeed emission monitoring (GEM) unit. The data were analysed to estimate daily methane production (DMP; g/day) and derived methane yield (MY; g/kg dry matter intake (DMI)). A one-compartment dose model of spot emission rate v. time since the preceding meal was compared with the models of Wood (1967) and Dijkstra et al. (1997) and the average of spot measures. Fitted values for DMP were calculated from the area under the curves. Two methods of relating methane and feed intakes were then studied: the classical calculation of MY as DMP/DMI (kg/day); and a novel method of estimating DMP from time and size of preceding meals using either the data for only the two meals preceding a spot measurement, or all meals for 3 days prior. Two approaches were also used to estimate DMP from spot measurements: fitting of splines on a 'per-animal per-day' basis and an alternate approach of modelling DMP after each feed event by least squares (using Solver), summing (for each animal) the contributions from each feed event by best-fitting a one-compartment model. Time since the preceding meal was of limited value in estimating DMP. Even when the meal sizes and time intervals between a spot measurement and all feeding events in the previous 72 h were assessed, only 16.9% of the variance in spot emission rate measured by GEM was explained by this feeding information. While using the preceding meal alone gave a biased (underestimate) of DMP, allowing for a longer feed history removed this bias. A power analysis taking into account the sources of variation in DMP indicated that to obtain an estimate of DMP with a 95% confidence interval within 5% of the observed 64 days mean of spot measures would require 40 animals measured over 45 days (two spot measurements per day) or 30 animals measured over 55 days. These numbers suggest that spot measurements could be made in association with feed efficiency tests made over 70 days. Spot measurements of enteric emissions can be used to define DMP but the number of animals and samples are larger than are needed when day-long measures are made.