232 research outputs found

    Lattice permutations and Poisson-Dirichlet distribution of cycle lengths

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    We study random spatial permutations on Z^3 where each jump x -> \pi(x) is penalized by a factor exp(-T ||x-\pi(x)||^2). The system is known to exhibit a phase transition for low enough T where macroscopic cycles appear. We observe that the lengths of such cycles are distributed according to Poisson-Dirichlet. This can be explained heuristically using a stochastic coagulation-fragmentation process for long cycles, which is supported by numerical data.Comment: 18 pages, 14 figure

    Luminosities and mass-loss rates of SMC and LMC AGB stars and Red Supergiants

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    (Abridged) Dust radiative transfer models are presented for 101 carbon stars and 86 oxygen-rich evolved stars in the Magellanic Clouds for which 5-35 \mum\ {\it Spitzer} IRS spectra are available. The spectra are complemented with available optical and infrared photometry to construct the spectral energy distribution. A minimisation procedure is used to fit luminosity, mass-loss rate and dust temperature at the inner radius. Different effective temperatures and dust content are also considered. Periods from the literature and from new OGLE-III data are compiled and derived. The O-rich stars are classified in foreground objects, AGB stars and Red Super Giants. For the O-rich stars silicates based on laboratory optical constants are compared to "astronomical silicates". Overall, the grain type by Volk & Kwok (1988) fit the data best. However, the fit based on laboratory optical constants for the grains can be improved by abandoning the small-particle limit. The influence of grain size, core-mantle grains and porosity are explored. Relations between mass-loss rates and luminosity and pulsation period are presented and compared to the predictions of evolutionary models, those by Vassiliadis & Wood (1993) and their adopted mass-loss recipe, and those based on a Reimers mass-loss law with a scaling of a factor of five. The Vassiliadis & Wood models describe the data better, although there are also some deficiencies, in particular to the maximum adopted mass-loss rate. The OGLE-III data reveal an O-rich star in the SMC with a period of 1749 days. Its absolute magnitude of Mbol=8.0M_{\rm bol}= -8.0 makes it a good candidate for a super-AGB star.Comment: A&A accepte

    Bridge to the future: Important lessons from 20 years of ecosystem observations made by the OzFlux network

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    In 2020, the Australian and New Zealand flux research and monitoring network, OzFlux, celebrated its 20th anniversary by reflecting on the lessons learned through two decades of ecosystem studies on global change biology. OzFlux is a network not only for ecosystem researchers, but also for those ‘next users’ of the knowledge, information and data that such networks provide. Here, we focus on eight lessons across topics of climate change and variability, disturbance and resilience, drought and heat stress and synergies with remote sensing and modelling. In distilling the key lessons learned, we also identify where further research is needed to fill knowledge gaps and improve the utility and relevance of the outputs from OzFlux. Extreme climate variability across Australia and New Zealand (droughts and flooding rains) provides a natural laboratory for a global understanding of ecosystems in this time of accelerating climate change. As evidence of worsening global fire risk emerges, the natural ability of these ecosystems to recover from disturbances, such as fire and cyclones, provides lessons on adaptation and resilience to disturbance. Drought and heatwaves are common occurrences across large parts of the region and can tip an ecosystem\u27s carbon budget from a net CO2 sink to a net CO2 source. Despite such responses to stress, ecosystems at OzFlux sites show their resilience to climate variability by rapidly pivoting back to a strong carbon sink upon the return of favourable conditions. Located in under-represented areas, OzFlux data have the potential for reducing uncertainties in global remote sensing products, and these data provide several opportunities to develop new theories and improve our ecosystem models. The accumulated impacts of these lessons over the last 20 years highlights the value of long-term flux observations for natural and managed systems. A future vision for OzFlux includes ongoing and newly developed synergies with ecophysiologists, ecologists, geologists, remote sensors and modellers

    Bridge to the future: Important lessons from 20 years of ecosystem observations made by the OzFlux network

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    In 2020, the Australian and New Zealand flux research and monitoring network, OzFlux, celebrated its 20th anniversary by reflecting on the lessons learned through two decades of ecosystem studies on global change biology. OzFlux is a network not only for ecosystem researchers, but also for those ‘next users’ of the knowledge, information and data that such networks provide. Here, we focus on eight lessons across topics of climate change and variability, disturbance and resilience, drought and heat stress and synergies with remote sensing and modelling. In distilling the key lessons learned, we also identify where further research is needed to fill knowledge gaps and improve the utility and relevance of the outputs from OzFlux. Extreme climate variability across Australia and New Zealand (droughts and flooding rains) provides a natural laboratory for a global understanding of ecosystems in this time of accelerating climate change. As evidence of worsening global fire risk emerges, the natural ability of these ecosystems to recover from disturbances, such as fire and cyclones, provides lessons on adaptation and resilience to disturbance. Drought and heatwaves are common occurrences across large parts of the region and can tip an ecosystem's carbon budget from a net CO2 sink to a net CO2 source. Despite such responses to stress, ecosystems at OzFlux sites show their resilience to climate variability by rapidly pivoting back to a strong carbon sink upon the return of favourable conditions. Located in under-represented areas, OzFlux data have the potential for reducing uncertainties in global remote sensing products, and these data provide several opportunities to develop new theories and improve our ecosystem models. The accumulated impacts of these lessons over the last 20 years highlights the value of long-term flux observations for natural and managed systems. A future vision for OzFlux includes ongoing and newly developed synergies with ecophysiologists, ecologists, geologists, remote sensors and modellers.</p

    Measurement of the τ\tau Lepton Polarization and its Forward-Backward Asymmetry from Z0Z^{0} Decays

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    Effect of blood glucose level on standardized uptake value (SUV) in F-18- FDG PET-scan : a systematic review and meta-analysis of 20,807 individual SUV measurements

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    Objectives To evaluate the effect of pre-scan blood glucose levels (BGL) on standardized uptake value (SUV) in F-18-FDG-PET scan. Methods A literature review was performed in the MEDLINE, Embase, and Cochrane library databases. Multivariate regression analysis was performed on individual datum to investigate the correlation of BGL with SUVmax and SUVmean adjusting for sex, age, body mass index (BMI), diabetes mellitus diagnosis, F-18-FDG injected dose, and time interval. The ANOVA test was done to evaluate differences in SUVmax or SUVmean among five different BGL groups (200 mg/dl). Results Individual data for a total of 20,807 SUVmax and SUVmean measurements from 29 studies with 8380 patients was included in the analysis. Increased BGL is significantly correlated with decreased SUVmax and SUVmean in brain (p <0.001, p <0.001,) and muscle (p <0.001, p <0.001) and increased SUVmax and SUVmean in liver (p = 0.001, p = 0004) and blood pool (p=0.008, p200 mg/dl had significantly lower SUVmax. Conclusion If BGL is lower than 200mg/dl no interventions are needed for lowering BGL, unless the liver is the organ of interest. Future studies are needed to evaluate sensitivity and specificity of FDG-PET scan in diagnosis of malignant lesions in hyperglycemia.Peer reviewe

    Author Correction: Native diversity buffers against severity of non-native tree invasions.

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    Native diversity buffers against severity of non-native tree invasions

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    Determining the drivers of non-native plant invasions is critical for managing native ecosystems and limiting the spread of invasive species1,2^{1,2}. Tree invasions in particular have been relatively overlooked, even though they have the potential to transform ecosystems and economies3,4^{3,4}. Here, leveraging global tree databases5,6,7^{5,6,7}, we explore how the phylogenetic and functional diversity of native tree communities, human pressure and the environment influence the establishment of non-native tree species and the subsequent invasion severity. We find that anthropogenic factors are key to predicting whether a location is invaded, but that invasion severity is underpinned by native diversity, with higher diversity predicting lower invasion severity. Temperature and precipitation emerge as strong predictors of invasion strategy, with non-native species invading successfully when they are similar to the native community in cold or dry extremes. Yet, despite the influence of these ecological forces in determining invasion strategy, we find evidence that these patterns can be obscured by human activity, with lower ecological signal in areas with higher proximity to shipping ports. Our global perspective of non-native tree invasion highlights that human drivers influence non-native tree presence, and that native phylogenetic and functional diversity have a critical role in the establishment and spread of subsequent invasions

    The global biogeography of tree leaf form and habit.

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    Understanding what controls global leaf type variation in trees is crucial for comprehending their role in terrestrial ecosystems, including carbon, water and nutrient dynamics. Yet our understanding of the factors influencing forest leaf types remains incomplete, leaving us uncertain about the global proportions of needle-leaved, broadleaved, evergreen and deciduous trees. To address these gaps, we conducted a global, ground-sourced assessment of forest leaf-type variation by integrating forest inventory data with comprehensive leaf form (broadleaf vs needle-leaf) and habit (evergreen vs deciduous) records. We found that global variation in leaf habit is primarily driven by isothermality and soil characteristics, while leaf form is predominantly driven by temperature. Given these relationships, we estimate that 38% of global tree individuals are needle-leaved evergreen, 29% are broadleaved evergreen, 27% are broadleaved deciduous and 5% are needle-leaved deciduous. The aboveground biomass distribution among these tree types is approximately 21% (126.4 Gt), 54% (335.7 Gt), 22% (136.2 Gt) and 3% (18.7 Gt), respectively. We further project that, depending on future emissions pathways, 17-34% of forested areas will experience climate conditions by the end of the century that currently support a different forest type, highlighting the intensification of climatic stress on existing forests. By quantifying the distribution of tree leaf types and their corresponding biomass, and identifying regions where climate change will exert greatest pressure on current leaf types, our results can help improve predictions of future terrestrial ecosystem functioning and carbon cycling

    Native diversity buffers against severity of non-native tree invasions.

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    Determining the drivers of non-native plant invasions is critical for managing native ecosystems and limiting the spread of invasive species1,2. Tree invasions in particular have been relatively overlooked, even though they have the potential to transform ecosystems and economies3,4. Here, leveraging global tree databases5-7, we explore how the phylogenetic and functional diversity of native tree communities, human pressure and the environment influence the establishment of non-native tree species and the subsequent invasion severity. We find that anthropogenic factors are key to predicting whether a location is invaded, but that invasion severity is underpinned by native diversity, with higher diversity predicting lower invasion severity. Temperature and precipitation emerge as strong predictors of invasion strategy, with non-native species invading successfully when they are similar to the native community in cold or dry extremes. Yet, despite the influence of these ecological forces in determining invasion strategy, we find evidence that these patterns can be obscured by human activity, with lower ecological signal in areas with higher proximity to shipping ports. Our global perspective of non-native tree invasion highlights that human drivers influence non-native tree presence, and that native phylogenetic and functional diversity have a critical role in the establishment and spread of subsequent invasions
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