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Studies were undertaken to determine the combined environmental effects of two temperature regimes (14/11 ℃, 17/14 ℃ day/night) and duration of postinoculation high humidity on progression of white leaf spot, caused by Neopseudocercosporella capsellae, in rapeseed (Brassica napus) at each of two different plant growth stages. Overall, percentage disease indices were significantly affected by temperature, high humidity duration, plant growth stage, and host cultivar (all p < 0.001). There were significant two‐way interactions of temperature regime with plant age (p < 0.001) and with host cultivar (p < 0.01), and significant three‐way interactions of high humidity duration with growth stage and host cultivar (p = 0.01) and with temperature and host cultivar (p = 0.03). At cotyledon stage, mean percentage cotyledon disease index was 38.2 at 17/14 ℃ day/night, and 33.1 at 14/11 ℃. At fourth leaf stage, mean percentage leaf disease index was 32.0 at 14/11 ℃ but 17.5 at 17/14 ℃. Disease severity increased with increasing duration of high humidity. Results explain why this disease is more prevalent and severe in Australia following longer durations of high humidity; why disease at cotyledon stage is largely independent of temperature if seasonal temperature ranges between 11 and 17 ℃; and why more severe leaf infection (e.g., at fourth leaf stage) can be attributed to cooling winter conditions between autumn and winter. Studies suggest current/predicted climate changes across southern Australia of increasingly warmer autumn‐winter temperatures and decreasing growing‐season (May–August) precipitation will lessen severity of future epidemics. [ABSTRACT FROM AUTHOR]

Ammonia, high temperature and high humidity have adverse effects on animals during long distance livestock export from Australia to the Middle East, but none of these is effectively measured currently. On the basis of data maps obtained on two voyages of live sheep export, this study determined sampling strategies for ammonia, temperature and humidity measurement on the vessel. The difference between predicted high and low ammonia sites on the shipment could be detected with approximately 5 measurement sites of each. Margins of error were determined, which suggested that dry bulb temperature could be measured with 6–8 measurement sites, but even 20 measurement sites were not sufficient to measure relative humidity. For the vessel recorded, considerably more ammonia measurement sites are required on closed decks than on open decks, with less variation for temperature measurement. The number of pens measured contributed more to the variance of ammonia and temperature measurement than the number of sampling locations within each pen on open decks. This study highlights the importance of a suitable sampling strategy to measure ammonia, temperature and relative humidity on board ship during live export. [ABSTRACT FROM AUTHOR]

Hygrothermal modelling is increasingly used to inform building envelope design. A key input for these calculations is the material's vapour diffusion properties. Respecting a growing international concern, this research has questioned the appropriateness of the current test method to establish construction material for vapour diffusion properties. This article reports on the empirical measurement of the vapour diffusion properties of two vapour-permeable building membranes commonly used in Australia residential systems when subjected to variable relative humidity conditions. The method involved completing dry cup and wet cup standard tests as specified in ISO 12572, (23 °C and 50% relative humidity RH). Further tests were then conducted as temperature remained at 23 °C but the relative humidity changed to 35%, 65% and 80%, respectively, in order to know if the diffusion properties are the same or change with varying relative humidity. The results from the wet cup and dry cup tests under different relative humidity conditions were non-linear and different. These results indicate vapour-permeable membranes behave differently when exposed to different relative humidity conditions. In conclusion, this research demonstrates that the current vapour resistivity test method is inadequate, hence the need to establish more detailed diffusion resistivity properties in different humidity ranges that represent conditions experienced within a building's external envelope. [ABSTRACT FROM AUTHOR]

Previous research has identified a relationship between climate and occurrence of SARS‐CoV and MERS‐CoV cases, information that can be used to reduce the risk of infection. Using COVID‐19 notification and postcode data from New South Wales, Australia during the exponential phase of the epidemic in 2020, we used time series analysis to investigate the relationship between 749 cases of locally acquired COVID‐19 and daily rainfall, 9 a.m. and 3 p.m. temperature, and 9 a.m. and 3 p.m. relative humidity. Lower 9 a.m. relative humidity (but not rainfall or temperature) was associated with increased case occurrence; a reduction in relative humidity of 1% was predicted to be associated with an increase of COVID‐19 cases by 6.11%. During periods of low relative humidity, the public health system should anticipate an increased number of COVID‐19 cases. [ABSTRACT FROM AUTHOR]

We examined a recent notion that differences in echolocation call frequency amongst geographic groups of constant frequency (CF)-emitting bats is the result of a trade-off between maximising prey detection range at lower frequencies and enhancing small-prey resolution at higher frequencies in different atmospheric (relative humidity; RH) environments. Isolated populations of the endemic Australian orange leaf-nosed bat Rhinonicteris aurantia were used as an example since geographic isolation in different environments has been a precursor to differences in their characteristic echolocation call frequencies (mean difference c. 6 kHz; means of 114.64 and 120.99 kHz). The influence of both atmospheric temperature and RH on maximum prey detection range was explored through mathematical modelling. This revealed that temperature was of similar importance to relative humidity and that under certain circumstances, each could reduce the effect of the other on ultrasound attenuation rates. The newly developed models contain significant conceptual improvements in method compared to other recent approaches, and can be applied to the situation of any other species of bat. For a given set of atmospheric conditions, the prey detection range of R. aurantia was reduced slightly when call frequency increased by 6 kHz, but an increase in RH, temperature or both reduced detection range significantly. A similar trend was also evident in prey detection volume ratios calculated for the same conditions. Spatial volume ratios were applied to assess the impact of changed atmospheric conditions and prey size on foraging ecology. Reductions in detection range associated with increases in RH and/or temperature also varied in relation to the size (cross sectional area) of insect prey. Modelling demonstrated that small (6 kHz) movements in call frequency could not compensate for the changes in prey detection range and spatial detection volumes that result from significant changes in atmospheric temperature or RH. The notion that differences in RH are the primary cause leading to adaptive evolution and speciation in CF-emitting bats by precipitating intraspecific differences in the mean call frequency of geographically isolated bat populations was not supported by the results of this case study., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

There is growing evidence that climatic factors could influence the evolution of the current COVID‐19 pandemic. Here, we build on this evidence base, focusing on the southern hemisphere summer and autumn period. The relationship between climatic factors and COVID‐19 cases in New South Wales, Australia was investigated during both the exponential and declining phases of the epidemic in 2020, and in different regions. Increased relative humidity was associated with decreased cases in both epidemic phases, and a consistent negative relationship was found between relative humidity and cases. Overall, a decrease in relative humidity of 1% was associated with an increase in cases of 7–8%. Overall, we found no relationship with between cases and temperature, rainfall or wind speed. Information generated in this study confirms humidity as a driver of SARS‐CoV‐2 transmission. [ABSTRACT FROM AUTHOR]

Introduction: Pressure injuries are a preventable yet highly prevalent health concern. Wheelchair cushion prescription can have significant implications for wheelchair users' risk of pressure injury development, which can impact functional abilities and quality of life. The efficacy of a wheelchair cushion to redistribute pressure has been well‐researched, but the efficacy to manage the microclimate is less clear, particularly in warm‐hot environments. The aim of this study was to systematically review studies examining the effect of wheelchair cushions on temperature, moisture and thermal perception to determine which cushions are superior to improve these responses. Method: A systematic review with meta‐analyses of randomised cross‐over and randomised control trials of wheelchair cushion interventions on measures of temperature, moisture, and thermal perception was conducted. Results: Eight studies were identified that met the eligibility criteria and six meta‐analyses were conducted. Pooled analyses identified a significantly lower temperature on foam‐gel cushions compared to air cushions (MD = 0.80, 95% CI: 0.31, 1.29; p = 0.002) and a significantly lower temperature on foam‐gel cushions compared to foam cushions (SMD = 0.76, 95%CI; 0.45, 1.06; p < 0.00001). Pooled analyses also demonstrated significantly lower relative humidity (i.e., moisture) on foam cushions compared to foam‐gel cushions (p = 0.02). Differences in thermal perception were inconclusive due to limited data found. Conclusion: It is clear that not one cushion is ideal in managing all aspects of microclimate, as foam‐gel cushions were the superior cushion to manage temperature and foam cushions were the superior cushion to manage moisture. This article provides occupational therapists and other health professionals with evidence‐based information to assist with wheelchair cushion prescription that minimises the temperature and moisture accumulation, and associated risk of pressure injury for wheelchair users. [ABSTRACT FROM AUTHOR]

Macadamia (Macadamia integrifolia and M. tetraphylla and their hybrids) is a tree nut crop affected by Botryosphaeria branch dieback. The disease results in branch and tree death in commercial orchards, so reducing the productivity of the Australian macadamia industry. There is a dearth of knowledge of the disease cycle in macadamia, which confounds disease management. This study investigated the dynamics of pathogen inoculum associated with Botryosphaeria branch dieback and the influence of environmental factors (temperature, rainfall and relative humidity) on the seasonal spore release within the orchards. Diseased and asymptomatic plant parts from macadamia trees were collected each season for 3 years in commercial orchards. Fungal structures (pycnidia and pseudothecia) mainly were (71%) observed on symptomatic wood samples. A comparison of the number of spores released from the fungal structures between summer and autumn revealed high concentrations of Lasiodiplodia pseudotheobromae from diseased wood (4.8 × 104 conidia/cm2) and Neofusicoccum luteum from blighted leaves (2.1 × 103 conidia/cm2). The peak airborne conidia dispersal period, quantified using microscopy and quantitative PCR assays, was consistently detected after rainfall and strongly associated with relative humidity over 70% and temperatures between 20 and 27°C during summer and autumn. Botryosphaeriaceae isolates obtained from the pycnidia on the macadamia trees caused severe branch dieback symptoms when inoculated on detached macadamia twigs, which suggests both airborne and rain‐splashed spores from fungal structures on the trees contribute to the disease in macadamia orchards. [ABSTRACT FROM AUTHOR]

1. A strong relationship between the oxygen isotope composition (expressed as δ18O) of body water and relative humidity has been demonstrated for a number of mammalian herbivores with low drinking water requirements, including kangaroos. Consequently, it has been suggested that the oxygen isotope composition of preserved mammal remains may be used to reconstruct past relative humidity. Other physiological, environmental and ecological factors may also influence mammalian δ18O, thereby confounding the climatic signal, yet these factors have been rigorously examined in few taxa. 2. We examined sources of variation in the δ18O of tooth enamel, assumed to reflect δ18O of body water, of kangaroos ( Macropus spp.) collected throughout Australia. 3. Relative humidity explained a large proportion of the variation in enamel δ18O, a finding that is consistent with previous studies. However, we also found a previously unreported interaction between mean annual temperature and relative humidity. At lower temperatures, the relationship between enamel δ18O and relative humidity was much steeper than at higher temperatures. 4. This may be a consequence of the Peclét effect in plant leaves, whereby high transpiration rates diminish the 18O enrichment of bulk leaf water. It is likely that this interaction is also present in other herbivores with low drinking water requirements. 5. We found little evidence that δ18O varied consistently between molars, suggesting that a ‘weaning effect’ is either absent or swamped by seasonal variation in precipitation δ18O. 6. We suggest that the oxygen isotope composition of preserved kangaroo remains cannot be used to reconstruct relative humidity unless ambient air temperature can be reliably estimated. [ABSTRACT FROM AUTHOR]

Recently, global epidemic models that use climatological factors have been proposed to explain influenza activities for both temperate and tropical regions. In this paper, these global models were extended by including interactions of climatological factors. This study was aimed to estimate the relative benefits of such interactions in explaining the global influenza epidemics. The effects of four climatological factors on laboratory-confirmed influenza cases were investigated, i.e., weekly temperature, precipitation, absolute humidity and relative humidity. It was found that countries in Europe and Australia have higher forecast skill, indicating the stronger relationship of influenza with climatological factors, than regions in other continents. The influenza activities of 47 (83%) countries can be explained with a closer match using multi-factor interactions along with original factors than only using the original factors. The temperate countries are characterized by the interaction of factors of temperature and absolute/relative humidity. In contrast, the interaction of factors of precipitation and absolute/relative humidity are dominant in tropical countries. [ABSTRACT FROM AUTHOR]

The global demand for energy is significantly impacted by the consumption patterns within the building sector. As such, the importance of energy simulation and prediction is growing exponentially. This research leverages Building Information Modelling (BIM) methodologies, creating a synergy between traditional software methods and algorithm-driven approaches for comprehensive energy analysis. The study also proposes a method for monitoring select energy management factors, a step that could potentially pave the way for the integration of digital twins in energy management systems. The research is grounded in a case study of a newly constructed educational building in New South Wales, Australia. The digital physical model of the building was created using Autodesk Revit, a conventional software for BIM methodology. EnergyPlus, facilitated by OpenStudio, was employed for the traditional software-based energy analysis. The energy analysis output was then used to develop preliminary algorithm models using regression strategies in Python. In this regression analysis, the temperature and relative humidity of each energy unit were used as independent variables, with their energy consumption being the dependent variable. The sigmoid algorithm model, known for its accuracy and interpretability, was employed for advanced energy simulation. This was combined with sensor data for real-time energy prediction. A basic digital twin (DT) example was created to simulate the dynamic control of air conditioning and lighting, showcasing the adaptability and effectiveness of the system. The study also explores the potential of machine learning, specifically reinforcement learning, in optimizing energy management in response to environmental changes and usage conditions. Despite the current limitations, the study identifies potential future research directions. These include enhancing model accuracy and developing complex algorithms to boost energy efficiency and reduce costs. [ABSTRACT FROM AUTHOR]

In Australia, summer brings intense, bright sunlight with high ultraviolet (UV) radiation and hot temperatures, which might impact free-range hens' ranging outside. To determine how range use was correlated with different sunlight variables and weather factors, a study was carried out on three commercial free-range layer farms during the summer/autumn period (December-May) across diverse regions of Australia in Tasmania (TAS), Queensland (QLD), and Western Australia (WA). Hens' range distribution was determined by counting the number of hens in the direct sunlight ('sun') or 'cloud' and shaded areas ('sun-shade' or 'cloud-shade', in sunny or cloudy conditions, respectively) using image snapshots taken at 30 min intervals from video recordings of a portion of one shed comprising 20,000–30,000 hens on each farm during the production phase of the laying cycle. The solar radiation spectrum [UV radiation (UVAB) (288–432 nm), photosynthetically active radiation (PAR; visible light) (400–700 nm), and total solar radiation (TSR) (285 nm-3000 nm)] and weather data (ambient temperature and relative humidity) were recorded through an on-site weather station. Data were analysed separately due to discrepancies between the farms' layouts. The effects of time of day and months on range use were analysed using General Linear Models in JMP® 16.0 and the relationship of sunlight and weather variables with hens' distribution in 'sun'/'sun-shade' and 'cloud'/'cloud-shade' in sunny and cloudy conditions respectively was determined by fitting linear ridge regression models using the 'lmridge' package in R. Overall, the time of day and month had significant effects on hens' distribution on the range (all p < 0.0001). Hens' range occupancy in the 'sun' decreased during the midday period with gradual increases in the late afternoon to evening, and the opposite pattern in the 'sun-shade'. A linear increase in the number of hens on the range over the months indicated the seasonal effects on hen ranging patterns. Temperature, UVAB and PAR were the most important factors for discouraging hens' range use in the 'sun' suggesting free-range systems in Australia should be designed to account for the extreme sunlight using adequate shade for optimum ranging across summer. [ABSTRACT FROM AUTHOR]

Purpose: To describe the physiological (resting core temperature, exercising heart rate, and sweat rate) and psychophysical (rating of perceived exertion, thermal sensation, and thermal comfort) responses to a short-term heat acclimatization (HA) training camp in elite female rugby sevens athletes. Methods: Nineteen professional female rugby sevens athletes participated in a 5-day HA camp in Darwin, Australia (training average: 32.2°C and 58% relative humidity). Training involved normal team practice prescribed by appropriate staff. Markers of physiological and psychophysical adaptations to HA were collected at various stages during the camp. Partial eta-squared effect sizes (from linear mixed-effects models), rank-biserial correlations (from Freidman tests), and P values were used to assess changes across the protocol. Results: Resting core temperature did not significantly change. Exercising heart rate showed a large and significant reduction from day 1 to day 5 (175 [13] vs 171 [12] beats·min−1), as did sweat rate (1.1 [0.3] vs 1.0 [0.2] L·h–1). Thermal sensation showed a large and significant reduction between day 1 and day 5 (median [interquartile range] = 5 [5–5.5] vs 4.5 [4–5]). Changes in rating of perceived exertion and thermal comfort were unclear. Conclusions: Beneficial cardiovascular adaptations were observed simultaneously across a full squad of elite female rugby sevens players (without expensive facilities/equipment or modifying training content). However, beneficial changes in resting core temperature, sweat rate, and thermal/effort perceptions likely require a greater thermal impulse. These data contribute to the development of evidence-informed practice for minimal effective HA doses in female team-sport athletes, who are underrepresented in the current research. [ABSTRACT FROM AUTHOR]

Foehn winds have been a focus of research in mid‐latitude mountainous regions for more than 150 years, where their onset is typically associated with warm, dry, and gusty winds. This research has now extended into high latitude regions, yet research of foehn winds in subtropical and tropical regions remains scarce. Here we present results from the first investigation of foehn winds in the subtropics of Southeast Queensland (SEQ), Australia. Analysis of meteorological records found that foehn winds occur throughout the year with peak frequency and duration in late winter (August) associated with the passage of shortwave troughs over southern Australia. Modeling of wind fields and atmospheric boundary layer conditions for three case studies was conducted using the Weather Research and Forecasting (WRF) model. Results showed foehn events in SEQ can be associated with mountain waves and hydraulic jump features in the lee of topographic barriers. Over lee slopes, acceleration of wind speeds and topographic channeling of foehn winds was found to occur, along with substantial increases in air temperature, and decreases in relative humidity. Warming of the foehn airstream is believed to occur primarily through isentropic drawdown with a likely contribution from surface sensible heat flux. Recommendations for future research are made in light of the importance of foehn winds to wildfire management and mitigation in SEQ. Plain Language Summary: Foehn winds form as airflow associated with the passage of large‐scale weather systems descends over the lee slopes of mountains and escarpments. These warm, dry, and gusty winds significantly change the meteorology in the lee of mountains and escarpments causing increases in air temperature, wind speed and decreases in humidity. While foehn winds have been a focus of mountain meteorology in mid‐latitude regions for more than 150 years, research of foehn in other climate zones is scarce. Here we present results from the first investigation of foehn winds in the subtropics of Southeast Queensland (SEQ), Australia—a region where foehn winds significantly increase the threat of wildfires. Results show that foehn winds in this region are most common in late winter (August) with the passage of shortwave troughs over southern Australia. Using the Weather Research and Forecasting (WRF) model we find that foehn wind events in SEQ may be associated with mountain waves and other dynamical features in the lee of topography. We suggest avenues for future foehn wind research in SEQ given their importance to wildfire management and mitigation. Key Points: Subtropical foehn winds are accurately modeled using the Weather Research of Forecasting modelFoehn warming of +10 to +14°C was simulated and caused by isentropic drawdownModeling showed mountain wave and hydraulic jump features in trans‐barrier flow [ABSTRACT FROM AUTHOR]

Background: Climate projections signal longer fire seasons and an increase in the number of dangerous fire weather days for much of the world including Australia. Aims: Here we argue that heatwaves, dynamic fire–atmosphere interactions and increased fuel availability caused by drought will amplify potential fire behaviour well beyond projections based on calculations of afternoon forest fire danger derived from climate models. Methods: We review meteorological dynamics contributing to enhanced fire behaviour during heatwaves, drawing on examples of dynamical processes driving fire behaviour during the Australian Black Summer bushfires of 2019–20. Results: Key dynamical processes identified include: nocturnal low-level jets, deep, unstable planetary boundary layers and fire–atmosphere coupling. Conclusions: The future scenario we contend is long windows of multi-day fire events where overnight suppression is less effective and fire perimeters will expand continuously and aggressively over multiple days and nights. Implications: Greater overnight fire activity and multi-day events present strategic and tactical challenges for fire management agencies including having to expand resourcing for overnight work, manage personnel fatigue and revise training to identify conditions conducive to unusually active fire behaviour overnight. Effective messaging will be critical to minimise accidental fire ignition during heatwaves and to alert the community to the changing fire environment Heatwaves, dynamic fire–atmosphere interactions and increased fuel availability caused by drought are likely to amplify fire behaviour under climate change. We review meteorological dynamics contributing to enhanced fire behaviour during heatwaves using examples from the 2019–20 Australian Black Summer bushfires and examine potential challenges posed for future fire management. [ABSTRACT FROM AUTHOR]

O'Connor, FK, Doering, TM, Minett, GM, Reaburn, PR, Bartlett, JD and Coffey, VG. Effect of divergent solar radiation exposure with outdoor versus indoor training in the heat: implications for performance. J Strength Cond Res 36(6): 1622–1628, 2022—The aim of this study was to determine physiological and perceptual responses and performance outcomes when completing high-intensity exercise in outdoor and indoor hot environments with contrasting solar radiation exposure. Seven cyclists and 9 Australian Football League (AFL) players undertook cycling trials in hot conditions (≥30 °C) outdoors and indoors. Cyclists completed 5 × 4 minutes intervals (∼80% peak power output [PPO]) with 2 minutes recovery (∼40% PPO) before a 20-km self-paced ride. Australian Football League players completed a standardized 20 minutes warm-up (∼65% mean 4-minute power output) then 5 × 2 minutes maximal effort intervals. Heart rate (HR), PO, ratings of perceived exertion (RPE), thermal comfort (TC), and thermal sensation (TS) were recorded. Core (Tc) and skin temperature (Tsk) were monitored in cyclists alone. In both studies, ambient temperature, relative humidity, and solar radiation were monitored outdoors and matched for ambient temperature and relative humidity indoors, generating different wet bulb globe temperature (WBGT) for cyclists, but the similar WBGT for AFL players through higher relative humidity indoors. The statistical significance was set at p ≤ 0.05. Cyclists' HR (p = 0.05), Tc (p = 0.03), and Tsk (p = 0.03) were higher outdoors with variable effects for increased RPE, TS, and TC (d = 0.2–1.3). Power output during intervals was not different between trials, but there were small-moderate improvements in cyclists' PO and 20-km time indoors (d = 0.3–0.6). There was a small effect (d = 0.2) for AFL players' mean PO to increase outdoors for interval 4 alone (p = 0.04); however, overall there were small-moderate effects for lower RPE and TS indoors (d = 0.2–0.5). Indoor training in hot conditions without solar radiation may promote modest reductions in physiological strain and improve performance capacity in well-trained athletes. [ABSTRACT FROM AUTHOR]

Reconstructed weather datasets, such as reanalyses based on model output with data assimilation, often show systematic biases in magnitude when compared with observations. Postprocessing approaches can help adjust the distribution so that the reconstructed data resemble the observed data as closely as possible. In this study, we have compared various statistical bias-correction approaches based on quantile–quantile matching to correct the data from the Twentieth Century Reanalysis, version 2c (20CRv2c), with observation-based data. Methods included in the comparison utilize a suite of different approaches: a linear model, a median-based approach, a nonparametric linear method, a spline-based method, and approaches that are based on the lognormal and Weibull distributions. These methods were applied to daily data in the Australian region for rainfall, maximum temperature, relative humidity, and wind speed. Note that these are the variables required to compute the forest fire danger index (FFDI), widely used in Australia to examine dangerous fire weather conditions. We have compared the relative errors and performances of each method across various locations in Australia and applied the approach with the lowest mean-absolute error across multiple variables to produce a reliable long-term bias-corrected FFDI dataset across Australia. The spline-based data correction was found to have some benefits relative to the other methods in better representing the mean FFDI values and the extremes from the observed records for many of the cases examined here. It is intended that this statistical bias-correction approach applied to long-term reanalysis data will help enable new insight on climatological variations in hazardous phenomena, including dangerous wildfires in Australia extending over the past century. [ABSTRACT FROM AUTHOR]

Context: Exercise in hot environments increases body temperature and thermoregulatory strain. However, little is known regarding the magnitude of effect that ambient temperature (Ta), relative humidity (RH), and solar radiation individually have on team-sport athletes. Purpose: To determine the effect of these individual heat-stress variables on team-sport training performance and recovery. Methods: Professional Australian Rules Football players (N = 45) undertook 8-wk preseason training producing a total of 579 outdoor field-based observations with Ta, RH, and solar radiation recorded at every training session. External load (distance covered, in m/min; percentage high-speed running [%HSR] >14.4 km/h) was collected via a global positioning system. Internal load (ratings of perceived exertion and heart rate) and recovery (subjective ratings of well-being and heart-rate variability [root mean square of the successive differences]) were monitored throughout the training period. Mixed-effects linear models analyzed relationships between variables using standardized regression coefficients. Results: Increased solar-radiation exposure was associated with reduced distance covered (−19.7 m/min, P <.001), %HSR (−10%, P <.001) during training and rMSSD 48 h posttraining (−16.9 ms, P =.019). Greater RH was associated with decreased %HSR (−3.4%, P =.010) but increased percentage duration >85% HRmax (3.9%, P <.001), ratings of perceived exertion (1.8 AU, P <.001), and self-reported stress 24 h posttraining (−0.11 AU, P =.002). In contrast, higher Ta was associated with increased distance covered (19.7 m/min, P <.001) and %HSR (3.5%, P =.005). Conclusions: The authors show the importance of considering the individual factors contributing to thermal load in isolation for team-sport athletes and that solar radiation and RH reduce work capacity during team-sport training and have the potential to slow recovery between sessions. [ABSTRACT FROM AUTHOR]

Glycaspis brimblecombei is an invasive insect species that specifically feeds on Eucalyptus leaves. Native from Australia, this species has spread to several countries becoming a major Eucalyptus pest. Even though its specific endoparasitoid Psyllaephagus bliteus has been present in Argentina since 2005, little is known about its ecology in the region. In this work we assess P. bliteus population development on Eucalypus camaldulensis and identify the meteorological variables associated with changes in its abundance. Furthermore, we study the level of natural parasitism in the field, and the density dependence relationship between P. bliteus and G. brimblecombei. We find that P. bliteus is present throughout the year with a maximum abundance at the end of spring-beginning of summer. Changes in its abundance are associated with temperature and relative humidity although it cannot be ruled out that this is due to an effect of climate on the density of its host. The highest levels of parasitism were registered when psyllid population was minimal, while density dependence analysis detected an inverse relationship between P. bliteus and its host. [ABSTRACT FROM AUTHOR]

With the frequent occurrence of extreme climates around the world, the frequency of regional wildfires is also on the rise, which poses a serious threat to the safety of human life, property, and regional ecosystems. To investigate the role of extreme climates in the occurrence and spread of wildfires, we combined precipitation, evapotranspiration, soil moisture (SM), maximum temperature (MT), relative humidity, plant canopy water, vapor pressure deficit, and a combined hydrological drought index based on six Gravity Recovery and Climate Experiment (GRACE) and its follow-on (GRACE-FO) products to study the relationship between climate change and wildfires across Australia between 2003 and 2020. The results show that Australia's wildfires are mainly concentrated in the northern region, with a small number being distributed along the southeastern coast. The high burned months are September (2.5941 × 106 ha), October (4.9939 × 106 ha), and November (3.8781 × 106 ha), while the years with a larger burned area are 2011 (79.95 × 106 ha) and 2012 (78.33 × 106 ha) during the study period. On a seasonal scale, the terrestrial water storage change and the hydrometeorological factors have the strong correlations with burned area, while for only the drought index, SM and MT are strongly related to burned area on an interannual scale. By comparing the data between the high burned and normal years, the impact of droughts on wildfires is achieved through two aspects: (1) the creation of a dry atmospheric environment, and (2) the accumulation of natural combustibles. Extreme climates affect wildfires through the occurrence of droughts. Among them, the El Niño–Southern Oscillation has the greatest impact on drought in Australia, followed by the Pacific Decadal Oscillation and the Indian Ocean Dipole (correlation coefficients are −0.33, −0.31, and −0.23, respectively), but there is little difference among the three. The proposed hydrological drought index in our study has the potential to provide an early warning of regional wildfires. Our results have a certain reference significance for comprehensively understanding the impact mechanism of extreme climates on regional wildfires and for establishing an early warning system for regional wildfires. [ABSTRACT FROM AUTHOR]

The present study aims to investigate the acute performance and physiological responses, with specific reference to muscle oxygenation, to ambient air temperature manipulation during repeated-sprint training in hypoxia (RSH). Thirteen male team-sport players completed one familiarisation and three experimental sessions at a simulated altitude of ∼3000 m (FIO2 0.144). Air temperatures utilised across the three experimental sessions were: 20°C, 35°C and 40°C (all 50% relative humidity). Participants performed 3 × 5 × 10-s maximal cycle sprints, with 20-s passive recovery between sprints, and 5 min active recovery between sets. There were no differences between conditions for cycling peak power, mean power, and total work (p>0.05). Peak core temperature (Tc) was not different between conditions (38.11 ± 0.36°C). Vastus lateralis muscle deoxygenation during exercise and reoxygenation during recovery was of greater magnitude in 35°C and 40°C than 20°C (p<0.001 for all). There was no condition × time interaction for Tc, skin temperature, pulse oxygen saturation, heart rate, rating of perceived exertion and thermal sensation (P>0.05). Exercise-induced increases in blood lactate concentration were higher in 35°C and 40°C than 20°C (p=0.010 and p=0.001, respectively). Integrating ambient temperatures up to 40°C into a typical RSH session had no detrimental effect on performance. Additionally, the augmented muscle oxygenation changes experienced during exercise and recovery in temperatures ≥35°C may indicate that the potency of RSH training is increased with additional heat. However, alterations to the training session may be required to generate a sufficient rise in Tc for heat training purposes. Highlights Heat exposure (35-40°C) did not affect mechanical performance during a typical RSH session. This indicates hot ambient temperature can be implemented during RSH, without negative consequence to training output. Hotter ambient conditions (35-40°C) likely result in greater muscle oxygenation changes during both exercise and recovery compared to temperate conditions. Although hotter sessions were perceived as more difficult and more thermally challenging, they did not further elevate Tc beyond that of temperate conditions. Accordingly, if intended to be used for heat acclimation purposes, alterations to the session may be required to increase heat load. [ABSTRACT FROM AUTHOR]

A traversing micro‐erosion meter (TMEM) was used to measure short‐term microtopographic changes on a supratidal rock surface at Marengo, Australia. In order to describe the characteristics of rock surface behaviour at different temporal scales, the TMEM site was monitored at 2‐hourly, daily and multiday (3.5 days) periods. The rock surface was highly dynamic at 2‐hourly scale, repeatedly falling and rising by up to 0.644 mm. Two‐hourly surface change was also characterised by spatial heterogeneity, with contraction and expansion occurring concurrently at centimetre scale across the rock surface. Two‐hourly microtopographic change was linked to the microclimate with significant relationships between surface movement and relative humidity (R2 = 0.27) and air temperature (R2 = 0.24). Expansion was observed across the rock surface when there was a fluctuation of 18% in relative humidity, and when cloudy the rock surface remained active during the day. Temporal variability in surface movement was also observed over a 24 h period with three distinct periods observed: falling (06:00–12:00), rising (12:00–20:00) and stable (20:00–06:00). The daily surface change underwent no net microtopographic change (no loss of material). In contrast, an overall contraction was observed at multiday scale. Rock surface behaviour in coastal environments is therefore complex with many cycles of expansion and contraction acting concurrently albeit at different temporal scales from hours to multiple days. © 2018 John Wiley & Sons, Ltd. Measured with a traversing micro‐erosion meter (TMEM), the microtopography of supratidal sandstone was observed to be highly dynamic in response to microclimatic variations at 2‐hourly scale, primarily driven by the fluctuating humidity. The rock surface underwent no net microtopographic loss of material at daily scale and could be divided into three periods of different movement trends: falling (06:00–12:00), rising (12:00–20:00) and stable (20:00–06:00), while an overall contraction occurred at multiday scale. [ABSTRACT FROM AUTHOR]

Navua sedge (Cyperus aromaticus (Ridley) Mattf. & Kukenth) is a significant agricultural and environmental weed found in tropical island countries including north Queensland, Australia. It is a prolific seed producer and consequently forms a high-density seedbank, and therefore understanding the longevity and persistence of the seeds can provide critical information required for the management of this species. A laboratory-controlled artificial ageing experiment was conducted where the seeds were exposed to a temperature of 45 °C and 60% relative humidity for 125 days. Seeds were removed at various times (1, 2, 5, 9, 20, 30, 50, 75, 100 and 125 days) and their viability determined through standard germination tests. It took 20 days in the artificial ageing environment for the seeds to decline to 50% viability which indicates that Navua sedge has relatively short-lived persistent seeds. These findings will assist in developing a better understanding of the seedbank dynamics of this invasive species, allowing managers to tactically implement control strategies and prepare budgets for ongoing treatments, and have implications for the duration and success of management programs. [ABSTRACT FROM AUTHOR]

Wildfires and hazard reduction burns produce smoke that contains pollutants including particulate matter. Particulate matter less than 2.5 µ m in diameter (PM 2.5) is harmful to human health, potentially causing cardiovascular and respiratory issues that can lead to premature deaths. PM 2.5 levels depend on environmental conditions, fire behaviour and smoke dispersal patterns. Fire management agencies need to understand and predict PM 2.5 levels associated with a particular fire so that pollution warnings can be sent to communities and/or hazard reduction burns can be timed to avoid the worst conditions for PM 2.5 pollution. We modelled PM 2.5 , measured at air quality stations in New South Wales (Australia) from ∼ 1400 d when individual fires were burning near air quality stations, as a function of fire and weather variables. Using Visible Infrared Imaging Radiometer Suite (VIIRS) satellite hotspots, we identified days when one fire was burning within 150 km of at least 1 of 48 air quality stations. We extracted ERA5 gridded weather data and daily active fire area estimates from the hotspots for our modelling. We created random forest models for afternoon, night and morning PM 2.5 levels to understand drivers of and predict PM 2.5. Fire area and boundary layer height were important predictors across the models, with temperature, wind speed and relative humidity also being important. There was a strong increase in PM 2.5 with decreasing distance, with a sharp increase when the fire was within 20 km. The models improve our understanding of the drivers of PM 2.5 from individual fires and demonstrate a promising approach to PM 2.5 model development. However, although the models predicted well overall, there were several large under-predictions of PM 2.5 that mean further model development would be required for the models to be deployed operationally. [ABSTRACT FROM AUTHOR]

Recent work attributing decadal regime changes in temperature to radiative forcing is extended to atmospheric moisture. Temperature, and specific and relative humidity (T, q, RH) from the HadISDH data set were analyzed for regime shifts using the bivariate test. Most shifts in q and T for global and northern hemisphere (NH), and tropical land occurred within a year of each other. Only one shift of q was recorded in the southern hemisphere (SH). RH increased in the NH in 1990–91 and decreased in a series of shifts from the late 1990s, while in the SH decreased from 2001. The tropics have remained neutral, shifting negative over land and positive over the ocean. The global decreases in 2001 and 2011 was −0.56%. Global RH from 32 climate models from the CMIP5 RCP4.5 archive all contained regime shifts but only 4 reached or exceeded the observed decreases by 2100, the earliest in 2056. Regime shifts in RH and fire danger over Australia are consistent with the SH decreases in RH, shifting within one year of global fire season length in 2002, showing that impacts are also being underestimated by current analyses. Methods for nonlinear attribution and the contributing processes for nonlinear change are discussed. These results show that developing a better understanding of nonlinear change in moisture-related climate risk is an urgent task. [ABSTRACT FROM AUTHOR]

A number of different methodologies are developed for examining the sensitivities of an index. These methodologies are applied to examine the characteristics of the Canadian Fire Weather Index FWI and the McArthur Forest Fire Danger Index FFDI using 8 years of gridded data throughout Australia. Percentile changes in input conditions show that the indices are similar to each other in that they are both most sensitive to wind speed, then secondly to relative humidity and thirdly to temperature. On a finer scale, a combination of the relationship between the indices and their partial derivatives shows that the FFDI is relatively less sensitive to wind speed and rainfall, and more sensitive to temperature and relative humidity, than the FWI. A method based on equilibrium values of the indices shows that the FFDI has a temperature threshold set by recent rainfall above which its sensitivity increases, resulting in some nonlinearity in its relationship with the FWI. The sensitivity differences between the indices mean that the indices are complementary in that they each respond to a somewhat different set of conditions, as is shown by examining a number of recent fire events. The fire events also reveal that index values associated with dangerous fire behaviour can vary greatly between different regions. Methods to reduce the consequences of this variation are examined, including the use of index percentiles. Copyright © 2009 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

This research assesses the potential impact of weekly weather variability on the incidence of cryptosporidiosis disease using time series zero-inflated Poisson (ZIP) and classification and regression tree (CART) models. Data on weather variables, notified cryptosporidiosis cases and population size in Brisbane were supplied by the Australian Bureau of Meteorology, Queensland Department of Health, and Australian Bureau of Statistics, respectively. Both time series ZIP and CART models show a clear association between weather variables (maximum temperature, relative humidity, rainfall and wind speed) and cryptosporidiosis disease. The time series CART models indicated that, when weekly maximum temperature exceeded 31°C and relative humidity was less than 63%, the relative risk of cryptosporidiosis rose by 13.64 (expected morbidity: 39.4; 95% confidence interval: 30.9–47.9). These findings may have applications as a decision support tool in planning disease control and risk-management programs for cryptosporidiosis disease. [ABSTRACT FROM AUTHOR]

Aim: We aimed to examine the impact of weather on hospital admissions with bronchiolitis in Australia and New Zealand.Methods: We collected data for inpatient admissions of infants aged 2-12 months to seven hospitals in four cities in Australia and New Zealand from 2009 until 2011. Correlation of hospital admissions with minimum daily temperature, wind speed, relative humidity and rainfall was examined using linear, Poisson and negative binomial regression analyses as well as general estimated equation models. To account for possible lag between exposure to weather and admission to hospital, analyses were conducted for time lags of 0-4 weeks.Results: During the study period, 3876 patients were admitted to the study hospitals. Hospital admissions showed strong seasonality with peaks in wintertime, onset in autumn and offset in spring. The onset of peak incidence was preceded by a drop in temperature. Minimum temperature was inversely correlated with hospital admissions, whereas wind speed was directly correlated. These correlations were sustained for time lags of up to 4 weeks. Standardised correlation coefficients ranged from -0.14 to -0.54 for minimum temperature and from 0.18 to 0.39 for wind speed. Relative humidity and rainfall showed no correlation with hospital admissions in our study.Conclusion: A decrease in temperature and increasing wind speed are associated with increasing incidence of bronchiolitis hospital admissions in Australia and New Zealand. [ABSTRACT FROM AUTHOR]

In recent months, the world has experienced the outbreak and spread of a new infectious disease, COVID-19. The spread of this disease has been so severe, and even many developed countries have struggled to manage this situation. However, some countries, such as China and Australia, have shown success in taking effective steps towards tackling the crisis. So far, some preventive measures to contain the spread of infection have emerged. Numerous studies have been undertaken worldwide in parallel in order to develop strategies to contain the virus, as well as to determine climatic or atmospheric conditions favoring COVID-19 spread. In this research, an artificial intelligence (AI) system has been adopted to assess the effective role of various environmental conditions in the spread of COVID-19. Temperature, relative humidity (RH), and UV index (UVI) of some affected countries were considered as input parameters while the total number of infected people is taken as the output variable. After plotting all available data as linguistic variables, a relationship is established between temperature, RH, UVI, and the number of infected people. From the surface graph, it can be stated that in addition to UVI, temperature and RH have a significant impact on the number of affected people. The maximum and minimum temperatures as well as other parameters are considered on the basis of mean values. [ABSTRACT FROM AUTHOR]

The current study aimed to identity the optimal low-cost stroller cooling strategies for use in hot and moderately humid summer weather. A commercially available stroller was instrumented to assess the key parameters of the thermal environment. The cooling efficacy of eight different stroller configurations was examined in a counterbalanced order across 16 hot summer days (air temperature (Ta) = 33.3 ± 4.1 °C; relative humidity = 36.7 ± 15%; black globe temperature = 43.9 ± 4.6 °C). Compared with a standard-practice stroller configuration, combining a moist muslin draping with a battery-operated clip-on fan provided optimal in-stroller cooling, reducing the end-trial air temperature by 4.7 °C and the wet bulb globe temperature (WBGT) by 1.4 °C. In contrast, in-stroller temperatures were substantially increased by draping a dry muslin (Ta = +2.6 °C; WBGT = +0.9 °C) or flannelette (Ta = +3.7 °C; WBGT = +1.4 °C) cloth over the stroller carriage. These findings provide empirical evidence which may inform guidance aimed at protecting infants during hot weather. Practitioner summary: This study examined the efficacy of traditional and novel stroller cooling strategies for use in hot and moderately humid weather. Covering the carriage with a dry muslin cloth substantially increased stroller temperatures and should be avoided. Evaporative cooling methods reduced in-stroller temperatures. A moist muslin cloth draping combined with a fan provided optimal stroller cooling. [ABSTRACT FROM AUTHOR]

This study evaluates the ability of machine learning algorithms to classify tropical depressions (TDs) and tropical storms (TSs) in the western region of the southwest Pacific Ocean (SWPO). Decision rules are generated to predict the environment required for a depression to fully develop into a mature storm, and the most influential predictors in the classification decision are ranked. TD and TS are discriminated based on a maximum sustained wind speed threshold (≥17 ms−1). Various aerosol, thermodynamic, and dynamic parameters are extracted closest to the initiation point of each non‐developing and developing sample. The covariates associated with each labelled sample are used to train a decision tree and random forest model. Results using a testing dataset suggest the random forest approach more accurately distinguishes between non‐developing and developing samples. The classification accuracy of the decision tree and random forest are 72% and 91%, respectively. Random forest outperformed the decision tree by providing higher accuracy in test data. The most important variables for binary classification are sea salt aerosol optical depth (AOD), 1,000 mb relative humidity, and sea surface temperature. AOD is a quantitative estimate of the aerosols presents in the air through the extinction of a ray of light as it passes through the atmosphere. Mean composite maps constructed in an unsupervised manner have been created for the most important variables identified by the random forest classifier during TD and TS events to highlight the difference in geophysical and aerosol variables' climatology during the two different classifications. This work will advance the risk management strategies for northeastern Australia and other SWPO basin islands to control their tropical cyclone related losses through prioritizing forecasting variables that are the strongest predictors of the strengthening of tropical depressions into tropical cyclones. [ABSTRACT FROM AUTHOR]

Wildfires and controlled hazard reduction burns produce smoke that contains pollutants including particulate 45 matter. Particulate matter less than 2.5 μm in diameter (PM2.5) is harmful to human health, potentially causing cardiovascular and respiratory issues that can lead to premature deaths. PM2.5 levels depend on environmental conditions, fire behaviour and smoke dispersal patterns. It is important for forest-fire management agencies to understand and predict PM2.5 levels associated with a particular fire, so that pollution warnings can be sent to communities and/or hazard reduction burns can be timed to avoid the worst conditions for PM2.5 pollution. We modelled PM2.5, measured at air quality stations in NSW Australia, from 1500 historical individual fires as a function of fire and weather variables. Using VIIRS satellite hotspots, we identified days where one fire was burning within 150 km of one of 48 air quality station. We extracted ERA5 gridded weather data and fire area estimates from the hotspots for our modelling. We created random forest models for afternoon, night and morning PM2.5 to understand drivers of and predict PM2.5. Fire area and boundary layer height were important predictors across the models, with temperature, wind speed and relative humidity also important. There was a strong increase in PM2.5 modelled with decreasing distance, with a sharp increase when the fire was within 15 km. The models improve understanding of drivers of PM2.5 from individual fires and demonstrate a promising approach to PM2.5 model development. However, although the models predicted well overall, there were several large under-predictions of PM2.5 that mean further model development would be required for the models to be deployed operationally. [ABSTRACT FROM AUTHOR]

In recent decades, southeast Australia has experienced both extreme drought and record-breaking rainfall, with devastating societal impacts. Variations in the Australian polar-front jet (PFJ) and the subtropical jet (STJ) determine, for example, the location and frequency of the cool season (April–September) weather systems influencing rainfall events and, consequently, water availability for the southern half of Australia. Changes in jet stream wind speeds also are important for aviation fuel and safety requirements. A split jet occurs when the single jet separates into the STJ and PFJ in the early cool season (April–May). This study focusses on split jet characteristics over Australian/New Zealand longitudes in recent decades. During the accelerated global warming from the mid-1990s, higher mean wind speeds were found in the PJF across the Australian region during June–September, compared to the STJ. In contrast, significant wind speed increases occur in the early cool season (April–May) at STJ latitudes, which straddle the East Coast of Australia and the adjacent Tasman Sea. These changes are linked to major changes in the mean atmospheric circulation, and they include relative vorticity and humidity, both being vital for the development of rain-bearing weather systems that affect the region. [ABSTRACT FROM AUTHOR]

The extent and severity of bushfires in a landscape are largely governed by meteorological conditions. An accurate understanding of the interactions of meteorological variables and fire behaviour in the landscape is very complex, yet possible. In exploring such understanding, we used 2693 high-confidence active fire points recorded by a Moderate Resolution Imaging Spectroradiometer (MODIS) sensor for nine different bushfires that occurred in Victoria between 1 January 2009 and 31 March 2009. These fires include the Black Saturday Bushfires of 7 February 2009, one of the worst bushfires in Australian history. For each fire point, 62 different meteorological parameters of bushfire time were extracted from Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA) data. These remote sensing and meteorological datasets were fused and further processed in assessing their relative importance using four different tree-based ensemble machine learning models, namely, Random Forest (RF), Fuzzy Forest (FF), Boosted Regression Tree (BRT), and Extreme Gradient Boosting (XGBoost). Google Earth Engine (GEE) and Landsat images were used in deriving the response variable–Relative Difference Normalised Burn Ratio (RdNBR), which was selected by comparing its performance against Difference Normalised Burn Ratio (dNBR). Our findings demonstrate that the FF algorithm utilising the Weighted Gene Coexpression Network Analysis (WGCNA) method has the best predictive performance of 96.50%, assessed against 10-fold cross-validation. The result shows that the relative influence of the variables on bushfire severity is in the following order: (1) soil moisture, (2) soil temperature, (3) air pressure, (4) air temperature, (5) vertical wind, and (6) relative humidity. This highlights the importance of soil meteorology in bushfire severity analysis, often excluded in bushfire severity research. Further, this study provides a scientific basis for choosing a subset of meteorological variables for bushfire severity prediction depending on their relative importance. The optimal subset of high-ranked variables is extremely useful in constructing simplified and computationally efficient surrogate models, which can be particularly useful for the rapid assessment of bushfire severity for operational bushfire management and effective mitigation efforts. [ABSTRACT FROM AUTHOR]

High-quality, standardized urban canopy layer observations are a worldwide necessity for urban climate and air quality research and monitoring. The Schools Weather and Air Quality (SWAQ) network was developed and distributed across the Greater Sydney region with a view to establish a citizen-centred network for investigation of the intra-urban heterogeneity and inter-parameter dependency of all major urban climate and air quality metrics. The network comprises a matrix of eleven automatic weather stations, nested with a web of six automatic air quality stations, stretched across 2779 km2, with average spacing of 10.2 km. Six meteorological parameters and six air pollutants are recorded. The network has a focus on Sydney's western suburbs of rapid urbanization, but also extends to many eastern coastal sites where there are gaps in existing regulatory networks. Observations and metadata are available from September 2019 and undergo routine quality control, quality assurance and publication. Metadata, original datasets and quality-controlled datasets are open-source and available for extended academic and non-academic use. Measurement(s) temperature of air • relative humidity • pressure of air • atmospheric wind speed • atmospheric wind direction • rainfall rate • sulphur dioxide • carbon monoxide • nitrogen dioxide • tropospheric ozone • pm10 • pm2.5 Technology Type(s) weather station • air quality station Sample Characteristic - Environment urban weather and pollution Sample Characteristic - Location Sydney, Australia [ABSTRACT FROM AUTHOR]

Aims: Flower blights (grey mould, green mould and dry flower) are important diseases of macadamia. Lack of information on pathogen biology and disease epidemiology in macadamia has hampered control options. Effects of climatic variables including temperature, relative humidity (RH) and vapour pressure deficit (VPD) on the abundance, germination and growth of conidia of four fungal pathogens that cause various flower blights in macadamia were studied. Methods and Results: Mycelial growth, sporulation, conidial germination and germ tube growth for five isolates each of Botrytis cinerea, Cladosporium cladosporioides, Pestalotiopsis macadamiae and Neopestalotiopsis macadamiae, at eight temperatures, seven RH and the corresponding VPD regimes were determined in vitro. The optimal climatic range of each of the four pathogens was validated during macadamia flowering periods in the 2019 and 2020 seasons by conidia detected and quantified using quantitative PCR. Several growth models were fitted to the data with high significance; predicted optima from these models ranged from 0.9 to 1.1 kPa VPD for P. macadamiae and N. macadamiae and <0.6 kPa VPD for B. cinerea and C. cladosporioides. Conclusions: This study showed that VPD, as a determinant of the fecundity and growth of the four fungal pathogens, was predictive of flower blight incidence in macadamia. The importance of temperature, RH and, thus, VPD for defining the conditions for infection and flower blight epidemics was established. Significance and Impact of the Study: This information provides a firm basis for the development of prediction tools for flower blights in macadamia. [ABSTRACT FROM AUTHOR]

Background and objective The 2006-2007 wildfire period was one of the most extensive and long lasting fires in Australian history with high levels of fine particulate matter ( PM2.5). Large populations were exposed to smoke for over 2 months. The study aimed to investigate the association between wildfire-related PM2.5 exposure and emergency department ( ED) visits for asthma. Methods A time-stratified case-crossover design was used to investigate associations between daily average PM2.5 and ED attendances for asthma from December 2006 to January 2007. ED data were obtained from the Victorian Emergency Minimum Dataset. Smoke dispersion during the wildfire event was modelled using a validated chemical transport model. Exposure data (daily average PM2.5, temperature and relative humidity) were modelled for the study period. Various lag periods were investigated. Results There were 2047 ED attendances for asthma during the study period. After adjusting for temperature and relative humidity, an interquartile range increase in PM2.5 levels of 8.6 μg/m3 was associated with an increase in ED attendances for asthma by 1.96% (95% CI: 0.02, 3.94) on the day of exposure. Lag periods up to 2 days prior did not show any association. A strong association was observed among women 20 years and older (5.08% 95% CI: 1.76, 8.51). Conclusions Wildfire-related PM2.5 was associated with increased risk of ED attendance for asthma during the wildfire event. It is important to understand the role of wildfire PM2.5 as a trigger for asthma presentations. [ABSTRACT FROM AUTHOR]

Objectives: This study investigated associations between weather conditions, physical activity, and sedentary time in primary school-aged children in Australia and Canada. Methods: Cross-sectional data on 9-11-year-old children from the Australian (n = 491 ) and Canadian (n = 524) sites of the International Study of Childhood Obesity, Lifestyle and the Environment were used. Minutes of daily moderate-to-vigorous-physical-activity (MVPA) and sedentary time were determined from 7-day, 24-h accelerometry (Actigraph GT3X+ triaxial accelerometer). Day-matched weather data (temperature, rainfall, snowfall, relative humidity, wind speed) were obtained from the closest weather station to participants' schools. Covariates included parental highest education level, day type, sex, and BMI z-scores. Generalized mixed model analyses allowing for clustering of participants within schools were completed. Scatterplots with Loess curves were created for maximum temperature, MVPA, and sedentary time. Results: Daily maximum temperature was significantly associated with MVPA and sedentary time in Australia (MVPA p = .05, sedentary p = .01) and Canada (p < .001, p = .001). Rainfall was negatively associated with MVPA in Australia (p < .001) and positively associated with sedentary time in Canada (p = .02). Conclusions: MVPA and sedentary time appear to be optimal when the maximum temperature ranges between 20°C and 25°C in both countries. The findings have implications for study design and interpretation for surveillance and intervention studies. [ABSTRACT FROM AUTHOR]

In this study we assessed the impact of climate variability on the Ross River virus (RRv) transmission and validated an epidemic-forecasting model in Cairns, Australia. Data on the RRv cases recorded between 1985 and 1996 were obtained from the Queensland Department of Health. Climate and population data were supplied by the Australian Bureau of Meteorology and the Australian Bureau of Statistics, respectively. The cross-correlation function (CCF) showed that maximum temperature in the current month and rainfall and relative humidity at a lag of 2 months were positively and significantly associated with the monthly incidence of RRv, whereas relative humidity at a lag of 5 months was inversely associated with the RRv transmission. We developed autoregressive integrated moving average (ARIMA) models on the data collected between 1985 to 1994, and then validated the models using the data collected between 1995 and 1996. The results show that the relative humidity at a lag of 5 months (p < 0.001) and the rainfall at a lag of 2 months (p < 0.05) appeared to play significant roles in the transmission of RRv disease in Cairns. Furthermore, the regressive forecast curves were consistent with the pattern of actual values. Key words: autoregressive integrated moving average, climate change, cross-correlation function, disease prediction, Ross River virus. Environ Health Perspect 109:1271-1273 (2001). [Online 28 November 2001] http://ehpnet1.niehs.nih.gov/docs/2001/109p1271-1273tong/abstr act.html [ABSTRACT FROM AUTHOR]

Small mammals are commonly surveyed using live trapping but the influence of weather conditions on trap success is largely unknown. This information is required to design and implement more effective field surveys and monitoring. We tested the influence of weather and moon phase on capture rates of small mammals in the Murray Mallee region of semi-arid Australia. We used extensive pitfall trapping data collected at 267 sites, totalling 54 492 trap-nights. We built regression models to explore the relationship between the capture rates of five species and daily meteorological conditions, and across families of mammals, including dasyurids, burramyids and rodents. A relationship common to several taxa was the positive influence of high winds (>20 km h−1) on capture rates. We also identified differences between taxa, with warmer overnight temperatures increasing capture rates of mallee ningaui but decreasing those of Bolam's mouse. This makes it difficult to determine a single set of 'optimal' meteorological conditions for surveying the entire community but points to conditions favourable to individual species and groups. We recommend that surveys undertaken in warmer months encompass a variety of meteorological conditions to increase capture rates and provide a representative sample of the small mammal community present in a landscape. Mallee small mammals are commonly surveyed using pitfall trapping but the influence of weather conditions on trap success is largely unknown. We tested the influence of weather and moon phase on capture rates of five species and three families of small mammals. Wind speeds >20 km h−1 positively influenced capture rates, but responses to other meteorological variables differed between taxa. We recommend that surveys encompass a variety of meteorological conditions to increase capture rates and effectively sample small mammal communities. [ABSTRACT FROM AUTHOR]

• Dead fuel moisture content assessed using a multi-modeling approach. • A global dataset of fire behavior experiments was used. • Vapor pressure deficit is a better predictor than temperature and relative humidity. • Semi-mechanistic models including vegetation type were the best approach. • Predicting fuel moisture content below 10 % was challenging. Dead fine fuel moisture content (FM) is one of the most important determinants of fire behavior. Fire scientists have attempted to effectively estimate FM for nearly a century, but we are still lacking broad scale evaluations of the different approaches for prediction. Here we tackle this problem by taking advantage or a recently compiled global fire behavior database (BONFIRE) gathering 1603 records of 1h (i.e., <6 mm diameter or thickness) dead fuel moisture content from measurements before experimental fires. We compared the results of models routinely used by different agencies worldwide, empirical models, semi-mechanistic models and also non-linear and machine learning approaches based on either temperature and relative humidity or vapor pressure deficit (VPD). A semi-mechanistic model based on VPD showed the best performance across all FM ranges and a historical model developed in Australia (MK5) was additionally recommended for low fuel moisture estimations. We also observed significant differences in FM dynamics between vegetation types with FM in grasslands more responsive to changes in atmospheric dryness than woody ecosystems. The addition of computational complexity through machine learning is not recommended since the gain in model fit is small relative to the increase in complexity. Future research efforts should concentrate on predictions at low FM (<10 %) as this is the range most significant for fire behavior and where the poorest model performance was observed. Model predictions are available from https://hcfm.shinyapps.io/shinyfmd/. [ABSTRACT FROM AUTHOR]

Oxygen (δ18O) and hydrogen (δ2H) isotope ratios, and their relationship to one another (d‐excess) are altered as water travels from the atmosphere to the land surface, into soils and plants and back to the atmosphere. Plants return water to the atmosphere through transpiration (evaporation through the stomata), which causes isotopic fractionation concentrating the heavier isotopes (18O and 2H) in the water that remains behind in the leaves. The degree of isotopic fractionation during transpiration is controlled largely by climate, and as a result can be predicted using process‐based models and climate data. The modelled transpirational isotopic fractionation can be applied to plant source water isotopic values to predict leaf water isotope ratios and generate maps of isotopic composition, or isoscapes. This approach of mechanistic modelling has been well demonstrated in the first generation of global leaf water isoscapes (PLoS One, 3(6), e2447, 2008). However, use of leaf water isoscapes in fields such as hydrology, ecology, and forensics requires a new generation of updated region‐specific isoscapes. Here, we generate leaf water isoscapes of δ18O, δ2H and d‐excess for Australia, the driest vegetated continent on Earth, where leaf water represents a critical water resource for ecosystems. These isoscapes represent an improvement over previous global isoscapes due to their higher resolution, region‐specific, empirically derived plant parameters, and non‐equilibrium corrections for water vapour isotopic composition. The new isoscapes for leaf water are evaluated relative to observed isotope ratios of leaf cellulose and cherry juice. The model predictions for annual average leaf water isotope ratios showed strong correlations with these plant tissues that integrate over time. Moreover, inclusion of region‐specific leaf temperature estimates and non‐equilibirum vapour corrections improved prediction accuracy. Regionally based isoscapes provide improved characterisations of average leaf water isotope ratios needed to support research in hydrology, plant ecophysiology, atmospheric science, ecology, and geographic provenancing of biological materials. [ABSTRACT FROM AUTHOR]

Hygrothermal assessment is essential to the production of healthy and energy efficient buildings. This has given rise to the demand for the development of a hygrothermal laboratory, as input data to hygrothermal modeling tools can only be sourced and validated through appropriate empirical measurements in a laboratory. These data are then used to quantify a building's dynamic characteristic moisture transport vis-a-vis a much more comprehensive energy performance analysis through simulation. This paper discusses the methods used to establish Australia's first hygrothermal laboratory for testing the water vapor resistivity properties of construction materials. The approach included establishing a climatically controlled hygrothermal test room with an automatic integrated system which controls heating, cooling, humidifying, and de-humidifying as required. The data acquisition for this hygrothermal test room operates with the installation of environmental sensors connected to specific and responsive programming codes. The room was successfully controlled to deliver a relative humidity of 50% with ±1%RH deviation and at 23 °C temperature with ±1 °C fluctuation during the testing of the water vapor diffusion properties of a pliable membrane common in Australian residential construction. To validate the potential of this testing facility, an independent measurement was also conducted at the Fraunhofer Institute of Building Physics laboratory (IBP) Holzkirchen, Germany for the diffusion properties of the same pliable membrane. The inter-laboratory testing results were subjected to statistical analysis of variance, this indicates that there is no significant difference between the result obtained in both laboratories. In conclusion, this paper demonstrates that a low-cost hygrothermally controlled test room can successfully replace the more expensive climatic chamber. [ABSTRACT FROM AUTHOR]

Background: Dengue fever (DF) outbreaks often arise from imported DF cases in Cairns, Australia. Few studies have incorporated imported DF cases in the estimation of the relationship between weather variability and incidence of autochthonous DF. The study aimed to examine the impact of weather variability on autochthonous DF infection after accounting for imported DF cases and then to explore the possibility of developing an empirical forecast system. Methodology/principal finds: Data on weather variables, notified DF cases (including those acquired locally and overseas), and population size in Cairns were supplied by the Australian Bureau of Meteorology, Queensland Health, and Australian Bureau of Statistics. A time-series negative-binomial hurdle model was used to assess the effects of imported DF cases and weather variability on autochthonous DF incidence. Our results showed that monthly autochthonous DF incidences were significantly associated with monthly imported DF cases (Relative Risk (RR):1.52; 95% confidence interval (CI): 1.01–2.28), monthly minimum temperature (oC) (RR: 2.28; 95% CI: 1.77–2.93), monthly relative humidity (%) (RR: 1.21; 95% CI: 1.06–1.37), monthly rainfall (mm) (RR: 0.50; 95% CI: 0.31–0.81) and monthly standard deviation of daily relative humidity (%) (RR: 1.27; 95% CI: 1.08–1.50). In the zero hurdle component, the occurrence of monthly autochthonous DF cases was significantly associated with monthly minimum temperature (Odds Ratio (OR): 1.64; 95% CI: 1.01–2.67). Conclusions/significance: Our research suggested that incidences of monthly autochthonous DF were strongly positively associated with monthly imported DF cases, local minimum temperature and inter-month relative humidity variability in Cairns. Moreover, DF outbreak in Cairns was driven by imported DF cases only under favourable seasons and weather conditions in the study. [ABSTRACT FROM AUTHOR]

The harsh Australian environment makes the use of steel reinforcement in concrete structures problematic on account of corrosion. The probability of corrosion damage will significantly increase in the years to come and will become a major problem not only in coastal regions but also in inland parts of Australia due to increasing carbon dioxide concentration, temperature, and relative humidity as a consequence of climate change. In the last two decades, glass fiber-reinforced polymer (GFRP) composite bars have become an alternative to steel reinforcement for reinforcing concrete structures exposed to harsh environments. The reinforcing material is noncorrodible, nonmagnetic, lightweight, and has high tensile strength, thus making it a viable reinforcing material for concrete structures. This paper provides the state-of-the-practice in the research, development, and application of GFRP bars, with the aim of properly informing the engineering community about this alternative, noncorrodible reinforcing technology. The paper also presents a strategy toward the development of fiber-reinforced polymer bar material specifications with the aim to ensure quality use and application of the GFRP material in a wide range of applications in Australia in the years to come. Moreover, the best practices and data presented in this paper will be very useful in the development of unified international standards and specifications for GFRP bars. [ABSTRACT FROM AUTHOR]

Purpose: To observe voluntary fluid and carbohydrate intakes and thermoregulatory characteristics of road cyclists during 2 multiday, multiple-stage races in temperate conditions. Methods: Ten internationally competitive male cyclists competed in 2 stage races (2009 Tour of Gippsland, T1, n = 5; 2010 Tour of Geelong, T2, n = 5) in temperate conditions (13.2-15.8°C; 54-80% relative humidity). Body mass (BM) was recorded immediately before and after each stage. Peak gastrointestinal temperature (TGI peak) was recorded throughout each stage. Cyclists recalled the types and volumes of fluid and food consumed throughout each stage. Results: Although fluid intake varied according to the race format, there were strong correlations between fluid intake and distance across all formats of racing, in both tours (r = .82, r = .92). Within a stage, the relationship between finishing time and fluid intake was trivial. Mean BM change over a stage was 1.3%, with losses >2% BM occurring on 5 out of 43 measured occasions and the fastest competitors incurring lower BM changes. Most subjects consumed carbohydrate at rates that met the new guidelines (30-60 g/h for 2-3 h, ~90 g/h for >3 h), based on event duration. There were consistent observations of TGI peak >39°C during stages of T1 (67%) and T2 (73%) despite temperate environmental conditions. Conclusion: This study captured novel effects of high-intensity stage racing in temperate environmental conditions. In these conditions, cyclists were generally able to find opportunities to consume fluid and carbohydrate to meet current guidelines. We consistently observed high TGI peak, which merits further investigation. [ABSTRACT FROM AUTHOR]

Simple Summary: Australian sunlight is intense, and may impact range use by free-range hens. Range design and management are important for optimising commercial layer farms where artificial shelters may offer protection for ranging hens. This study investigated preferences among 34–40-week-old hens for artificial shade cloth shelters of different densities, using two flocks on a commercial farm during the summer. Three types of sunlight-filtering shade cloth shelters, i.e., blocking 50%, 70%, and 90% of ultraviolet (UV) light, each with three replicates, were placed on the range for each flock. The number of hens under each shelter was counted at 30-min intervals using image snapshots from video recordings for 14 to 17 days. An on-site weather station recorded sunlight intensity across different spectra, ambient temperature, and relative humidity. During the day, hens generally preferred the 90%, followed by 70% and 50% sunlight-filtering shelters. However, fewer hens were observed underneath shelters during times of peak sun intensity. Shelter preferences were mostly impacted by ambient temperature in both flocks, with all sunlight spectra having different degrees of effect depending on the shelter type and flock. Overall, shelters comprising higher densities of sunlight-filtering artificial cloth were preferred by hens on the range, but these may not be sufficient to attract more hens outside during intense sunlight and hot climatic conditions. Extreme sunlight might be aversive to free-range laying hens, discouraging them from going outside. Range enrichment with artificial shelters may protect hens from sunlight and increase range use. The preferences of 34–40-week-old Hy-Line Brown laying hens for artificial shelters were assessed by counting the number of hens under three densities of individual shelters (three replicates/density) from video recordings for 14 to 17 days for two flocks. The artificial shelters used shade cloth marketed as blocking 50%, 70%, and 90% of ultraviolet light, although other sunlight wavelengths were also reduced. Different sunlight spectral irradiances (ultraviolet radiation (UVAB) (288–432 nm), photosynthetically active radiation (PAR) (400–700 nm), and total solar radiation (TSR) (285 nm–3000 nm), ambient temperature, and relative humidity were recorded with an on-site weather station. There was a significant interaction between sunlight-filtering shelter and time of day (both Flocks, p < 0.0001), i.e., hens preferred shelters with the highest amount of sunlight-filtering at most time points. Regression models showed that the most variance in shelter use throughout the day resulted from the ambient temperature in both flocks, while sunlight parameters had different degrees of effect depending on the shelter type and flock. However, fewer hens under the shelters during the midday period suggest that during periods of intense sunlight, hens prefer to remain indoors, and artificial structures might not be sufficient to attract more hens outside. [ABSTRACT FROM AUTHOR]

Fire management agencies use fire behaviour simulation tools to predict the potential spread of a fire in both risk planning and operationally during wildfires. These models are generally based on underlying empirical or quasi-empirical relations and rarely are uncertainties considered. Little attention has been given to the quality of the input data used during operational fire predictions. We examined the extent to which error in weather forecasts can affect fire simulation results. The study was conducted using data representing the State of Victoria in south-eastern Australia, including grassland and forest conditions. Two fire simulator software packages were used to compare fire growth under observed and forecast weather. We found that error in the weather forecast data significantly altered the predicted size and location of fires. Large errors in wind speed and temperature resulted in an overprediction of fire size, whereas large errors in wind direction resulted in an increased spatial error in the fire's location. As the fire weather intensified, fire predictions using forecast weather under predicted fire size, potentially resulting in greater risks to the community. These results highlight the importance of on-ground intelligence during wildfires and the use of ensembles to improve operational fire predictions. Fire simulators inform critical decisions for communities during wildfires. The sensitivity of these models to input data uncertainty is unknown. Fire area is most sensitive to error in temperature and wind speed, whereas location is most sensitive to error in wind direction. On-ground intelligence is vital for accurate fire predictions. [ABSTRACT FROM AUTHOR]

Occupancy-based monitoring programs rely on survey data to infer presence or absence of the target species. However, species may occupy a site and go undetected, leading to erroneous inference of absence ('false absence'). If detectability is influenced by the time of year or weather conditions, survey protocols can be adjusted to minimize the chance of false absences. In this study, detection probabilities for three amphibian species from south-eastern Australia were modelled using a Bayesian approach. For aural surveys, we compared basic models, which only included effects of survey date, duration and time of day on detection, to models including additional effects of weather. Model selection using deviance information criterion (DIC) suggested that the basic model was the most parsimonious for Crinia signifera, while models including relative humidity and water temperature were most supported for Limnodynastes dumerilii and L. tasmaniensis respectively. When predictive performance was assessed by cross validation, DIC results were largely matched for C. signifera and L. dumerilii, while models of detection for L. tasmaniensis were indistinguishable, AUC scores suggesting inadequate performance. We show how results such as these can be used to design surveys, developing protocols for individual surveys and estimating the number of surveys required under those protocols to achieve a threshold cumulative probability of detection. Conservation managers can use these models to maximize the efficiency of surveys. This will improve the accuracy of occupancy data, and reduce the risk of misdirected conservation actions resulting from false absences. [ABSTRACT FROM AUTHOR]

The gas-induced swelling behavior of coal is important when considering CO2 sequestration into coal seams or enhanced coalbed methane applications, but coals may also swell in the presence of moisture, or shrink on drying. In this paper we examine the moisture-swelling properties of coals from Australia and elsewhere. Results on the moisture uptake and corresponding swelling measurements are presented for 15 coals of various ranks (sub-bituminous and bituminous) at 22°C and atmospheric pressure. Measurements were made by exposing sample blocks of coal (nominally 30 × 10 × 10 mm) to relative humidities ranging from 0% to 97%. A selection of coals was also fully saturated in water. Moisture uptake at 97% relative humidity (RH) ranged from about 2.5% to more than 16% db. Maximum linear strain associated with the moisture sorption (measured at 97% RH) varied from about 0.2% to 1.3%, with lower rank coals showing the most swelling. In all cases, swelling was greater in the direction perpendicular to the bedding plane. These results correspond to volumetric swelling of about 0.5% to around 5%. Although exhibiting significant expansion, all of the samples returned to their original dimensions upon drying. Volumetric moisture sorption and the amount of swelling induced were found to be strongly correlated by a single linear expression that held for all of the coals examined. It was further found that the volume of the water adsorbed was linearly related to the pore space within the coal, however, at 97% relative humidity, only about 60% of the available pore space is occupied by water. Exposure to liquid water allowed the pores to completely fill; although for the lowest rank coals, the volume of water absorbed appeared to be slightly more than the corresponding pore volume. Despite the additional water uptake, immersion in water did not produce further swelling beyond that induced at 97% relative humidity. [ABSTRACT FROM AUTHOR]