Key physicochemical factors associated with microbial community composition and functions in Australian agricultural soils were identified. Soils from seven field sites, with varying long-term ...agricultural management regimes, were characterised physicochemically, on the basis of their bacterial and fungal community structures (using PCR-DGGE), and by assessing potential catabolic functions (MicroResp™). Soil type, rather than agricultural management practice, was the key determinant of microbial community structure and catabolic function (
P<0.05). Following multivariate analysis, soil pH was identified as the key habitat-selective physicochemical soil property associated with variation in biological diversity and profiles of organic substrate utilisation. In particular, the capacity of soils to catabolise different C-substrates was closely correlated (
ρ=0.604,
P=0.001) to pH. With decreasing pH, the catabolism of common low molecular weight organic compounds (especially cysteine and aspartic acid) declined, however catabolism of two others (lysine and arginine) increased. Shifts in the capacity of soil microbiota to cycle common organic compounds have implications for overall geochemical cycling of C and N in acidifying soils. The genetic structure of the bacterial communities in soil strongly correlated with pH (
ρ=0.722;
P=0.001) and that of soil fungi with pH and % sand (
ρ=0.323;
P=0.006). Catabolic function was more closely associated with the structure of the bacterial than fungal communities. This work has shown that soil pH is a primary driver of microbial diversity and function in soil. Agricultural management practices thereby act to selectively shift populations and functions against this background.
In this study, solid state 13C nuclear magnetic resonance (NMR) spectroscopy was used to explore the carbon-containing functional groups present in pyrogenic carbon (PyC) produced during different ...fire spread modes to forest litter fuels from a dry sclerophyll eucalypt forest burnt in a combustion wind tunnel. A replicated experimental study was performed using three different fire spread modes: heading fires (i.e. fires which spread with the wind), flanking fires (i.e. fires which spread perpendicular to the wind) and backing fires (i.e. fires which spread against the wind). In addition to 13C NMR measurements of PyC, detailed fire behaviour measurements were recorded during experiments. Experiments showed that heading fires produced significantly more aryl carbon in ash samples than flanking fires. All other experimental comparisons for burnt fuel samples involving different fire spread modes were statistically insignificant. Principal component analysis (PCA) was used to explore the relationship between 13C NMR functional groups and fire behaviour observations. Results from PCA indicate that maximising the residence time of high temperature combustion and the combustion factor (i.e. the fraction of pre-fire biomass consumed by fire) could be a method for increasing the amount of aryl carbon in PyC. Maximising the amount of aryl carbon could be beneficial for the overall PyC balance from fire, since more recalcitrant carbon (e.g. carbon with a higher aryl carbon content) that is not emitted to the atmosphere has been shown to have longer residence times in environmental media such as soils or sediments.
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•Nine experimental fires were conducted in a combustion wind tunnel facility.•Three fire spread modes with three replicates each were performed.•Properties of pyrogenic carbon were quantified using 13C NMR spectroscopy.•Heading fires produced more aryl carbon than flanking fires for ash samples.•Aryl carbon production is increased with a higher temperature residence time.
Gliomas are notoriously aggressive, malignant brain tumors that have variable response to treatment. These patients often have poor prognosis, informed primarily by histopathology. Mathematical ...neuro-oncology (MNO) is a young and burgeoning field that leverages mathematical models to predict and quantify response to therapies. These mathematical models can form the basis of modern "precision medicine" approaches to tailor therapy in a patient-specific manner. Patient-specific models (PSMs) can be used to overcome imaging limitations, improve prognostic predictions, stratify patients, and assess treatment response in silico. The information gleaned from such models can aid in the construction and efficacy of clinical trials and treatment protocols, accelerating the pace of clinical research in the war on cancer. This review focuses on the growing translation of PSM to clinical neuro-oncology. It will also provide a forward-looking view on a new era of patient-specific MNO.
The cycling of N in soil is supported both directly and indirectly by numerous microbial processes. These processes affect ecosystem fertility, but can also generate forms of N which have detrimental ...environmental impacts, such as N₂O. Understanding drivers of biological communities involved in key N-transformations is therefore of much interest. The effects of physicochemical and environmental properties on the relative size (abundance within total DNA pool) of biological communities involved in 3 key N transformations were investigated. Soils from 14 locations spanning a rainfall gradient across 3 agricultural regions (Clare, Mallee, Balaclava) were sampled, with samples taken from the surface and at depth from each site. Based on PCA of physicochemical and environmental properties, the soils fell into 2 distinct groupings: Clare and Mallee+Balaclava 'types'. The abundance of functional genes involved in N₂ fixation (nifH), ammonia oxidation (amoA), and nitrate reduction (narG) was quantified in DNA extracted from the soils using real-time PCR. The abundance of the nifH gene varied significantly with site (P=0.03) but not depth, and no regional association with nifH gene abundance was found. Multivariate analysis indicated that the abundance of nifH was positively correlated with soil total C (ρ=0.382; P=0.006). Similarly, the abundance of narG varied with site (P<0.001) and not soil depth. The abundance of narG was positively correlated with increasing rainfall (ρ=0.417; P=0.002). The abundance of amoA did not significantly vary between soils, but significantly decreased with soil depth (P=0.006). The abundance of amoA was negatively correlated with soil electrical conductivity and positively with organic C (combined ρ=0.44; P=0.003). Whereas there was no relationship between the abundance of nifH and amoA or narG, the abundance of amoA was positively correlated with the abundance of narG (P<0.001). These results indicate that the abundance of the N cycling genes is independently affected by different physicochemical or environmental properties. The interactions between soil, environment, and the functionally significant biological communities they support are complex. To gain fuller understanding of soil N cycling, the ecology of the various biological components affecting N-transformations must be investigated simultaneously.
Quantifying the content and composition of soil carbon in the laboratory is time-consuming, requires specialised equipment and is therefore expensive. Rapid, simple and low-cost accurate methods of ...analysis are required to support current interests in carbon accounting. This study was completed to develop national and state-based models capable of predicting soil carbon content and composition by coupling diffuse reflectance mid-infrared (MIR) spectra with partial least-squares regression (PLSR) analyses. Total, organic and inorganic carbon contents were determined and MIR spectra acquired for 20495 soil samples collected from 4526 locations from soil depths to 1m within Australia’s agricultural regions. However, all subsequent MIR/PLSR models were developed using soils only collected from the 0–10, 10–20 and 20–30cm depth layers. The extent of grinding applied to air-dried soil samples was found to be an important determinant of the variability in acquired MIR spectra. After standardisation of the grinding time, national MIR/PLSR models were developed using an independent test-set validation approach to predict the square-root transformed contents of total, organic and inorganic carbon and total nitrogen. Laboratory fractionation of soil organic carbon into particulate, humus and resistant forms was completed on 312 soil samples. Reliable national MIR/PLSR models were developed using cross-validation to predict the contents of these soil organic carbon fractions; however, further work is required to enhance the representation of soils with significant contents of inorganic carbon. Regional MIR/PLSR models developed for total, organic and inorganic carbon and total nitrogen contents were found to produce more reliable and accurate predictions than the national models. The MIR/PLSR approach offers a more rapid and more cost effective method, relative to traditional laboratory methods, to derive estimates of the content and composition of soil carbon and total nitrogen content provided that the soils are well represented by the calibration samples used to build the predictive models.
Co‐flowering plant species commonly share flower visitors, and thus have the potential to influence each other's pollination. In this study we analysed 750 quantitative plant–pollinator networks from ...28 studies representing diverse biomes worldwide. We show that the potential for one plant species to influence another indirectly via shared pollinators was greater for plants whose resources were more abundant (higher floral unit number and nectar sugar content) and more accessible. The potential indirect influence was also stronger between phylogenetically closer plant species and was independent of plant geographic origin (native vs. non‐native). The positive effect of nectar sugar content and phylogenetic proximity was much more accentuated for bees than for other groups. Consequently, the impact of these factors depends on the pollination mode of plants, e.g. bee or fly pollinated. Our findings may help predict which plant species have the greatest importance in the functioning of plant–pollination networks.
Nature play is growing in popularity as children's play spaces are transforming from traditional playgrounds into more nature-based play spaces with considerable financial and resource investment ...from government bodies. This has resulted in the re-development of children's play spaces to incorporate more natural elements such as trees, plants and rocks. Despite this, it is unclear whether there is empirical evidence to support claims that play in nature is beneficial for child health and development.
To conduct a systematic review examining the impacts of nature play on the health and developmental outcomes of children aged 2-12 years.
Seven electronic databases were searched (MEDLINE, ERIC, Embase, PsycINFO, The Cochrane Library, The Joanna Briggs Institute and Emcare) from inception to July/August 2018 (search updated July/August 2019). The Inclusion criteria were children aged 2-12 years with no health/developmental conditions. The exposure/intervention of interest was unstructured, free play in nature. Critical appraisal of included studies was conducted using the McMaster Critical Appraisal Tool. Descriptive synthesis was then undertaken using the NHMRC FORM Framework.
Out of 2927 articles identified, 16 studies met the inclusion criteria. The nature play exposure/intervention was heterogeneously described, and a plethora of outcome measures were used. Nature play had consistent positive impacts on physical activity outcomes and cognitive play behaviours (imaginative and dramatic play). However, there remain some concerns regarding the quality of the evidence base, heterogeneity in intervention description and parameters in the outcome measures used.
While the positive impacts of nature play were encouraging in terms of physical activity and cognitive development, nature play stakeholders should focus on producing a universal definition for nature play, the development of standardised outcome measures and the conduct of robust research designs. Implications of these findings suggest the need for the development of standardised guidelines to inform practice and policy in the design of children's play spaces in different contexts.
Background. Pollinators, which provide the agriculturally and ecologically essential service of pollination, are under threat at a global scale. Habitat loss and homogenisation, pesticides, parasites ...and pathogens, invasive species, and climate change have been identified as past and current threats to pollinators. Actions to mitigate these threats, e.g., agri-environment schemes and pesticide-use moratoriums, exist, but have largely been applied post-hoc. However, future sustainability of pollinators and the service they provide requires anticipation of potential threats and opportunities before they occur, enabling timely implementation of policy and practice to prevent, rather than mitigate, further pollinator declines. Methods.Using a horizon scanning approach we identified issues that are likely to impact pollinators, either positively or negatively, over the coming three decades. Results.Our analysis highlights six high priority, and nine secondary issues. High priorities are: (1) corporate control of global agriculture, (2) novel systemic pesticides, (3) novel RNA viruses, (4) the development of new managed pollinators, (5) more frequent heatwaves and drought under climate change, and (6) the potential positive impact of reduced chemical use on pollinators in non-agricultural settings. Discussion. While current pollinator management approaches are largely driven by mitigating past impacts, we present opportunities for pre-emptive practice, legislation, and policy to sustainably manage pollinators for future generations.
Malignant gliomas are incurable, primary brain neoplasms noted for their potential to extensively invade brain parenchyma. Current methods of clinical imaging do not elucidate the full extent of ...brain invasion, making it difficult to predict which, if any, patients are likely to benefit from gross total resection. Our goal was to apply a mathematical modeling approach to estimate the overall tumor invasiveness on a patient-by-patient basis and determine whether gross total resection would improve survival in patients with relatively less invasive gliomas.
In 243 patients presenting with contrast-enhancing gliomas, estimates of the relative invasiveness of each patient's tumor, in terms of the ratio of net proliferation rate of the glioma cells to their net dispersal rate, were derived by applying a patient-specific mathematical model to routine pretreatment MR imaging. The effect of varying degrees of extent of resection on overall survival was assessed for cohorts of patients grouped by tumor invasiveness.
We demonstrate that patients with more diffuse tumors showed no survival benefit (P = 0.532) from gross total resection over subtotal/biopsy, while those with nodular (less diffuse) tumors showed a significant benefit (P = 0.00142) with a striking median survival benefit of over eight months compared to sub-totally resected tumors in the same cohort (an 80% improvement in survival time for GTR only seen for nodular tumors).
These results suggest that our patient-specific, model-based estimates of tumor invasiveness have clinical utility in surgical decision making. Quantification of relative invasiveness assessed from routinely obtained pre-operative imaging provides a practical predictor of the benefit of gross total resection.
Although it is known that older drivers limit their driving, it is not known whether this self-regulation is related to actual driving ability. A sample of 104 older drivers, aged between 60 and 92, ...completed a questionnaire about driving habits and attitudes. Ninety of these drivers also completed a structured on-road driving test.
A measure of self-regulation was derived from drivers’ self-reported avoidance of difficult driving situations. The on-road driving test involved a standard assessment used to determine fitness to drive. Driving test scores for the study were based on the number of errors committed in the driving tests, with weightings given according to the seriousness of the errors.
The most commonly avoided difficult driving situations, according to responses on the questionnaire, were parallel parking and driving at night in the rain, while the least avoided situation was driving alone. Poorer performance on the driving test was not related to overall avoidance of difficult driving situations. Stronger relationships were found between driving ability and avoidance of specific difficult driving situations. These specific driving situations were the ones in which the drivers had low confidence and that the drivers were most able to avoid if they wished to.
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