159 research outputs found

    Phase diagram of calcium at high pressure and high temperature

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    Resistively heated diamond-anvil cells have been used together with synchrotron x-ray diffraction to investigate the phase diagram of calcium up to 50 GPa and 800 K. The phase boundaries between the Ca-I (fcc), Ca-II (bcc), and Ca-III (simple cubic, sc) phases have been determined at these pressure-temperature conditions, and the ambient temperature equation of state has been generated. The equation of state parameters at ambient temperature have been determined from the experimental compression curve of the observed phases by using third-order Birch-Murnaghan and Vinet equations. A thermal equation of state was also determined for Ca-I and Ca-II by combining the room-temperature Birch-Murnaghan equation of state with a Berman-type thermal expansion model.Part of the research was supported by the Spanish Government MINECO under Grants No. MAT2016-75586-C4-1/4P and No. MAT2015-71070-REDC.Peer reviewe

    Risk factor analysis and spatiotemporal CART model of cryptosporidiosis in Queensland, Australia

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    Background: It remains unclear whether it is possible to develop a spatiotemporal epidemic prediction model for cryptosporidiosis disease. This paper examined the impact of social economic and weather factors on cryptosporidiosis and explored the possibility of developing such a model using social economic and weather data in Queensland, Australia.Methods: Data on weather variables, notified cryptosporidiosis cases and social economic factors in Queensland were supplied by the Australian Bureau of Meteorology, Queensland Department of Health, and Australian Bureau of Statistics, respectively. Three-stage spatiotemporal classification and regression tree (CART) models were developed to examine the association between social economic and weather factors and monthly incidence of cryptosporidiosis in Queensland, Australia. The spatiotemporal CART model was used for predicting the outbreak of cryptosporidiosis in Queensland, Australia.Results: The results of the classification tree model (with incidence rates defined as binary presence/absence) showed that there was an 87% chance of an occurrence of cryptosporidiosis in a local government area (LGA) if the socio-economic index for the area (SEIFA) exceeded 1021, while the results of regression tree model (based on non-zero incidence rates) show when SEIFA was between 892 and 945, and temperature exceeded 32°C, the relative risk (RR) of cryptosporidiosis was 3.9 (mean morbidity: 390.6/100,000, standard deviation (SD): 310.5), compared to monthly average incidence of cryptosporidiosis. When SEIFA was less than 892 the RR of cryptosporidiosis was 4.3 (mean morbidity: 426.8/100,000, SD: 319.2). A prediction map for the cryptosporidiosis outbreak was made according to the outputs of spatiotemporal CART models.Conclusions: The results of this study suggest that spatiotemporal CART models based on social economic and weather variables can be used for predicting the outbreak of cryptosporidiosis in Queensland, Australia

    Climate-induced range shifts shaped the present and threaten the future genetic variability of a marine brown alga in the Northwest Pacific

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    Glaciation-induced environmental changes during the last glacial maximum (LGM) have strongly influenced species' distributions and genetic diversity patterns in the northern high latitudes. However, these effects have seldom been assessed on sessile species in the Northwest Pacific. Herein, we chose the brown alga Sargassum thunbergii to test this hypothesis, by comparing present population genetic variability with inferred geographical range shifts from the LGM to the present, estimated with species distribution modelling (SDM). Projections for contrasting scenarios of future climate change were also developed to anticipate genetic diversity losses at regional scales. Results showed that S. thunbergii harbours strikingly rich genetic diversity and multiple divergent lineages in the centre-northern range of its distribution, in contrast with a poorer genetically distinct lineage in the southern range. SDM hindcasted refugial persistence in the southern range during the LGM as well as post-LGM expansion of 18 degrees of latitude northward. Approximate Bayesian computation (ABC) analysis further suggested that the multiple divergent lineages in the centre-northern range limit stem from post-LGM colonization from the southern survived lineage. This suggests divergence due to demographic bottlenecks during range expansion and massive genetic diversity loss during post-LGM contraction in the south. The projected future range of S. thunbergii highlights the threat to unique gene pools that might be lost under global changes.UIDB/04326/2020 - PTDC/BIA-CBI/6515/2020 - DL57/2016/CP1361/CT0035info:eu-repo/semantics/publishedVersio

    Disturbance and the Dynamics of Coral Cover on the Great Barrier Reef (1995–2009)

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    Coral reef ecosystems worldwide are under pressure from chronic and acute stressors that threaten their continued existence. Most obvious among changes to reefs is loss of hard coral cover, but a precise multi-scale estimate of coral cover dynamics for the Great Barrier Reef (GBR) is currently lacking. Monitoring data collected annually from fixed sites at 47 reefs across 1300 km of the GBR indicate that overall regional coral cover was stable (averaging 29% and ranging from 23% to 33% cover across years) with no net decline between 1995 and 2009. Subregional trends (10–100 km) in hard coral were diverse with some being very dynamic and others changing little. Coral cover increased in six subregions and decreased in seven subregions. Persistent decline of corals occurred in one subregion for hard coral and Acroporidae and in four subregions in non-Acroporidae families. Change in Acroporidae accounted for 68% of change in hard coral. Crown-of-thorns starfish (Acanthaster planci) outbreaks and storm damage were responsible for more coral loss during this period than either bleaching or disease despite two mass bleaching events and an increase in the incidence of coral disease. While the limited data for the GBR prior to the 1980's suggests that coral cover was higher than in our survey, we found no evidence of consistent, system-wide decline in coral cover since 1995. Instead, fluctuations in coral cover at subregional scales (10–100 km), driven mostly by changes in fast-growing Acroporidae, occurred as a result of localized disturbance events and subsequent recovery

    Mining social mixing patterns for infectious disease models based on a two-day population survey in Belgium

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    <p>Abstract</p> <p>Background</p> <p>Until recently, mathematical models of person to person infectious diseases transmission had to make assumptions on transmissions enabled by personal contacts by estimating the so-called WAIFW-matrix. In order to better inform such estimates, a population based contact survey has been carried out in Belgium over the period March-May 2006. In contrast to other European surveys conducted simultaneously, each respondent recorded contacts over two days. Special attention was given to holiday periods, and respondents with large numbers of professional contacts.</p> <p>Methods</p> <p>Participants kept a paper diary with information on their contacts over two different days. A contact was defined as a two-way conversation of at least three words in each others proximity. The contact information included the age of the contact, gender, location, duration, frequency, and whether or not touching was involved.</p> <p>For data analysis, we used association rules and classification trees. Weighted generalized estimating equations were used to analyze contact frequency while accounting for the correlation between contacts reported on the two different days.</p> <p>A contact surface, expressing the average number of contacts between persons of different ages was obtained by a bivariate smoothing approach and the relation to the so-called next-generation matrix was established.</p> <p>Results</p> <p>People mostly mixed with people of similar age, or with their offspring, their parents and their grandparents. By imputing professional contacts, the average number of daily contacts increased from 11.84 to 15.70. The number of reported contacts depended heavily on the household size, class size for children and number of professional contacts for adults. Adults living with children had on average 2 daily contacts more than adults living without children. In the holiday period, the daily contact frequency for children and adolescents decreased with about 19% while a similar observation is made for adults in the weekend. These findings can be used to estimate the impact of school closure.</p> <p>Conclusion</p> <p>We conducted a diary based contact survey in Belgium to gain insights in social interactions relevant to the spread of infectious diseases. The resulting contact patterns are useful to improve estimating crucial parameters for infectious disease transmission models.</p

    On plexus representation of dissimilarities

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    Correspondence analysis has found widespread application in analysing vegetation gradients. However, it is not clear how it is robust to situations where structures other than a simple gradient exist. The introduction of instrumental variables in canonical correspondence analysis does not avoid these difficulties. In this paper I propose to examine some simple methods based on the notion of the plexus (sensu McIntosh) where graphs or networks are used to display some of the structure of the data so that an informed choice of models is possible. I showthat two different classes of plexus model are available. These classes are distinguished by the use in one case of a global Euclidean model to obtain well-separated pair decomposition (WSPD) of a set of points which implicitly involves all dissimilarities, while in the other a Riemannian view is taken and emphasis is placed locally, i.e., on small dissimilarities. I showan example of each of these classes applied to vegetation data

    Dissimilar responses of fungal and bacterial communities to soil transplantation simulating abrupt climate changes.

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    Both fungi and bacteria play essential roles in regulating soil carbon cycling. To predict future carbon stability, it is imperative to understand their responses to environmental changes, which is subject to large uncertainty. As current global warming is causing range shifts toward higher latitudes, we conducted three reciprocal soil transplantation experiments over large transects in 2005 to simulate abrupt climate changes. Six years after soil transplantation, fungal biomass of transplanted soils showed a general pattern of changes from donor sites to destination, which were more obvious in bare fallow soils than in maize cropped soils. Strikingly, fungal community compositions were clustered by sites, demonstrating that fungi of transplanted soils acclimatized to the destination environment. Several fungal taxa displayed sharp changes in relative abundance, including Podospora, Chaetomium, Mortierella and Phialemonium. In contrast, bacterial communities remained largely unchanged. Consistent with the important role of fungi in affecting soil carbon cycling, 8.1%-10.0% of fungal genes encoding carbon-decomposing enzymes were significantly (p &lt; 0.01) increased as compared with those from bacteria (5.7%-8.4%). To explain these observations, we found that fungal occupancy across samples was mainly determined by annual average air temperature and rainfall, whereas bacterial occupancy was more closely related to soil conditions, which remained stable 6 years after soil transplantation. Together, these results demonstrate dissimilar response patterns and resource partitioning between fungi and bacteria, which may have considerable consequences for ecosystem-scale carbon cycling

    Connectivity and systemic resilience of the Great Barrier Reef

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    Australia’s iconic Great Barrier Reef (GBR) continues to suffer from repeated impacts of cyclones, coral bleaching, and outbreaks of the coral-eating crown-of-thorns starfish (COTS), losing much of its coral cover in the process. This raises the question of the ecosystem’s systemic resilience and its ability to rebound after large-scale population loss. Here, we reveal that around 100 reefs of the GBR, or around 3%, have the ideal properties to facilitate recovery of disturbed areas, thereby imparting a level of systemic resilience and aiding its continued recovery. These reefs (1) are highly connected by ocean currents to the wider reef network, (2) have a relatively low risk of exposure to disturbances so that they are likely to provide replenishment when other reefs are depleted, and (3) have an ability to promote recovery of desirable species but are unlikely to either experience or spread COTS outbreaks. The great replenishment potential of these ‘robust source reefs’, which may supply 47% of the ecosystem in a single dispersal event, emerges from the interaction between oceanographic conditions and geographic location, a process that is likely to be repeated in other reef systems. Such natural resilience of reef systems will become increasingly important as the frequency of disturbances accelerates under climate change

    Bayesian Classification and Regression Trees for Predicting Incidence of Cryptosporidiosis

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    Background Classification and regression tree (CART) models are tree-based exploratory data analysis methods which have been shown to be very useful in identifying and estimating complex hierarchical relationships in ecological and medical contexts. In this paper, a Bayesian CART model is described and applied to the problem of modelling the cryptosporidiosis infection in Queensland, Australia. Methodology/Principal Findings We compared the results of a Bayesian CART model with those obtained using a Bayesian spatial conditional autoregressive (CAR) model. Overall, the analyses indicated that the nature and magnitude of the effect estimates were similar for the two methods in this study, but the CART model more easily accommodated higher order interaction effects. Conclusions/Significance A Bayesian CART model for identification and estimation of the spatial distribution of disease risk is useful in monitoring and assessment of infectious diseases prevention and control

    Mapping Oil and Gas Development Potential in the US Intermountain West and Estimating Impacts to Species

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    Many studies have quantified the indirect effect of hydrocarbon-based economies on climate change and biodiversity, concluding that a significant proportion of species will be threatened with extinction. However, few studies have measured the direct effect of new energy production infrastructure on species persistence. in the western US and translate the build-out scenarios into estimated impacts on sage-grouse. We project that future oil and gas development will cause a 7–19 percent decline from 2007 sage-grouse lek population counts and impact 3.7 million ha of sagebrush shrublands and 1.1 million ha of grasslands in the study area.Maps of where oil and gas development is anticipated in the US Intermountain West can be used by decision-makers intent on minimizing impacts to sage-grouse. This analysis also provides a general framework for using predictive models and build-out scenarios to anticipate impacts to species. These predictive models and build-out scenarios allow tradeoffs to be considered between species conservation and energy development prior to implementation
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