Implementation of a medical command and control team in Switzerland

In case of a major incident or disaster, the advance medical rescue command needs to manage several essential tasks simultaneously. These include the rapid deployment of ambulance, police, fire and evacuation services, and their coordinated activity, as well as triage and emergency medical care on site. The structure of such a medical rescue command is crucial for the successful outcome of medical evacuation at major incidents. However, little data has been published on the nature and structure of the command itself. This study presents a flexible approach to command structure, with two command heads: one emergency physician and one experienced paramedic. This approach is especially suitable for Switzerland, whose federal system allows for different structures in each canton. This article examines the development of these structures and their efficiency, adaptability and limitations with respect to major incident response in the French‐speaking part of the country.     

Plant growth rates and seed size: a re-evaluation

Small-seeded plant species are often reported to have high relative growth rate or RGR. However, because RGR declines as plants grow larger, small-seeded species could achieve higher RGR simply by virtue of their small size. In contrast, size-standardized growth rate or SGR factors out these size effects. Differences in SGR can thus only be due to differences in morphology, allocation, or physiology. We used nonlinear regression to calculate SGR for comparison with RGR for 10 groups of species spanning a wide range of life forms. We found that RGR was negatively correlated with seed mass in nearly all groups, but the relationship between SGR and seed mass was highly variable. We conclude that small-seeded species only sometimes possess additional adaptations for rapid growth over and above their general size advantage.     

Sterol production and phytosterol bioconversion in two species of heterotrophic protists, Oxyrrhis marina and Gyrodinium dominans

The kinetics and efficiency of sterol production and bioconversion of phytosterols in two heterotrophic protists Oxyrrhis marina and Gyrodinium dominans were examined by feeding them two different algal species (Rhodomonas salina and Dunaliella tertiolecta) differing in sterol profiles. R. salina contains predominantly brassicasterol (≅99%) and <2% cholesterol. The major sterols in D. tertiolecta are ergosterol (45–49%), 7-dehydroporiferasterol (29–31%) and fungisterol (21–26%). O. marina fed R. salina metabolized dietary brassicasterol to produce 22-dehydrocholesterol and cholesterol. O. marina fed D. tertiolecta metabolized dietary sterols to produce cholesterol, 22-dehydrocholesterol, brassicasterol and stigmasterol. G. dominans fed either R. salina or D. tertiolecta metabolized dietary sterols to make cholesterol, brassicasterol and a series of unknown sterols. When protists were fed R. salina, which contains cholesterol, the levels of cholesterol were increased to a magnitude of nearly 5- to 30-fold at the phytoplankton-heterotrophic protist interface, equivalent to a production of 172.5 ± 16.2 and 987.7 ± 377.7 ng cholesterol per mg R. salina carbon consumed by O. marina and G. dominans, respectively. When protists were fed D. tertiolecta, which contains no cholesterol, a net production of cholesterol by the protists ranged from 123.2 ± 30.6 to 871.8 ± 130.8 ng per mg algal C consumed. Cholesterol is not only the dominant sterol, but a critical precursor for many physiologically functional biochemicals in higher animal. As intermediates, these heterotrophic protists increase the amount of cholesterol at the phytoplankton–zooplankton interface available to higher trophic levels relative to zooplankton feeding on algae directly.     

COSMOS,a spatially explicit model to simulate the epidemiology of Cosmopolites sordidus in banana fields

A stochastic individual-based model called COSMOS was developed to simulate the epidemiology of banana weevil Cosmopolites sordidus, a major pest of banana fields. The model is based on simple rules of local movement of adults, egg laying of females, development and mortality, and infestation of larvae inside the banana plants. The biological parameters were estimated from the literature, and the model was validated at the small-plot scale. Simulated and observed distributions of attacks were similar except for five plots out of 18, using a Kolmogorov–Smirnov test. These exceptions may be explained by variation in predation of eggs and measurement error. An exhaustive sensitivity analysis using the Morris method showed that predation rate of eggs, demographic parameters of adults and mortality rate of larvae were the most influential parameters. COSMOS was therefore used to test different spatial arrangements of banana plants on the epidemiology of C. sordidus. Planting bananas in groups increased the time required to colonise plots but also the percentage of banana plants with severe attacks. Spatial heterogeneity of banana stages had no effect on time required to colonise plots but increased the mean level of attacks. Our model helps explain key factors of population dynamics and the epidemiology of this tropical pest.     

Modelling radiative balance in a row-crop canopy: Cross-row distribution of net radiation at the soil surface and energy available to clusters in a vineyard

Distribution of energy at the soil surface in a row-crop influences mainly soil temperature and water content, and therefore root activity, nitrogen mineralization and within canopy air temperature, which all affect plant physiology. In the case of a vineyard, it is also closely related to the energy available to the berries and therefore most influential for fruit quality. The aim of this study was to develop a simplified model of available energy distribution at the soil surface and at the bottom of the rows, where most of the clusters are located. Such a model would be helpful for optimising some aspects of row-crop management like training system choice, row geometry, leaf area density, and soil surface maintenance practices.The model simulated radiation balance at the soil surface, split up into downward and upward short- and long-wave fluxes. Row shadows were calculated at any point of the inter-row space, in interaction with actual row geometry and simplified porosity distribution within row volume. All hemispheric radiations (long-wave and diffuse solar radiation) were calculated according to view factors between the row and soil surfaces. Input variables were therefore incoming solar radiation over the canopy, air temperatures near the row walls and soil surface temperatures. Parameters were row geometry, dimensions and porosities.The model was validated in a 7 years old Merlot vineyard in the Médoc area, by comparing model predictions to measured net radiation (Rns) at five positions above the inter-row soil surface. Along the row sampling was achieved by a moving device carrying the net-radiometers. Structure of the vegetation was kept constant during the experiment and gap fraction parameters were derived from pictures of shadows at the soil surface. Since Rns measurements are impracticable directly at the soil surface and horizontal distribution of Rns is heterogeneous, comparison was performed by calculating net radiation at the actual measurement height which was close to average cluster height.Model prediction agreed with field measurement in most conditions, which suggests that all short- and long-wave radiation fluxes, as well as interactions with the canopy structure, were well described. Rns, energy available to clusters, and soil surface temperature variations were all mainly driven by shading due to the rows. Coupling the model to soil heat transfer and convective fluxes to the atmosphere models will help forecasting soil temperature distribution at the surface and in depth as well as canopy microclimate. The model will also be an essential part of a more elaborate model of cluster microclimate, a key determinant of berry quality.     

Radio (<Superscript>14</Superscript>C)- and fluorescent-doubly labeled silica nanoparticles for biological and environmental toxicity assessment

A new and efficient synthetic route to fluorescent and ¹⁴C-double-labeled silica-based nanoparticles (NPs) is described. The synthesis has been carried out using the “oil-in-water” micro-emulsion technique. Fluorescent and radioactive labeling have been achieved entrapping labeled poly(ethylene glycol) (PEG) molecules in the NPs. The produced particles have been analyzed by means of scanning electron microscopy, photon correlation spectroscopy, confocal microscopy, scintillation counting and oxidation/combustion experiments. Fluorescence quenching experiments confirm that the label is entrapped in the particles. The results presented suggest that the silica matrix does not block the β-radiations emitted from the labeled PEG molecules entrapped in the NPs.     

Response of tree growth to a changing climate in boreal central Canada: A comparison of empirical,process-based,and hybrid modelling approaches

The impact of 2 × CO₂ driven climate change on radial growth of boreal tree species Pinus banksiana Lamb., Populus tremuloides Michx. and Picea mariana (Mill.) BSP growing in the Duck Mountain Provincial Forest of Manitoba (DMPF), Canada, is simulated using empirical and process-based model approaches. First, empirical relationships between growth and climate are developed. Stepwise multiple-regression models are conducted between tree-ring growth increments (TRGI) and monthly drought, precipitation and temperature series. Predictive skills are tested using a calibration–verification scheme. The established relationships are then transferred to climates driven by 1× and 2 × CO₂ scenarios using outputs from the Canadian second-generation coupled global climate model. Second, empirical results are contrasted with process-based projections of net primary productivity allocated to stem development (NPP_s). At the finest scale, a leaf-level model of photosynthesis is used to simulate canopy properties per species and their interaction with the variability in radiation, temperature and vapour pressure deficit. Then, a top-down plot-level model of forest productivity is used to simulate landscape-level productivity by capturing the between-stand variability in forest cover. Results show that the predicted TRGI from the empirical models account for up to 56.3% of the variance in the observed TRGI over the period 1912–1999. Under a 2 × CO₂ scenario, the predicted impact of climate change is a radial growth decline for all three species under study. However, projections obtained from the process-based model suggest that an increasing growing season length in a changing climate could counteract and potentially overwhelm the negative influence of increased drought stress. The divergence between TRGI and NPP_s simulations likely resulted, among others, from assumptions about soil water holding capacity and from calibration of variables affecting gross primary productivity. An attempt was therefore made to bridge the gap between the two modelling approaches by using physiological variables as TRGI predictors. Results obtained in this manner are similar to those obtained using climate variables, and suggest that the positive effect of increasing growing season length would be counteracted by increasing summer temperatures. Notwithstanding uncertainties in these simulations (CO₂ fertilization effect, feedback from disturbance regimes, phenology of species, and uncertainties in future CO₂ emissions), a decrease in forest productivity with climate change should be considered as a plausible scenario in sustainable forest management planning of the DMPF.     

Roles of survival and dispersal in reintroduction success of Griffon vulture (Gyps fulvus).

The success of reintroduction programs greatly depends on the amount of mortality and dispersal of the released individuals. Although local environmental pressures are likely to play an important role in these processes, they have rarely been investigated because of the lack of spatial replicates of reintroduction. In the present study, we analyzed a 25-year data set encompassing 272 individuals released in five reintroduction programs of Griffon Vultures (Gyps fulvus) in France to examine the respective roles of survival and dispersal in program successes and failures. We use recent developments in multi-strata capture-recapture models to take into account tag loss in survival estimates and to consider and estimate dispersal among release areas. We also examined the effects of sex, age, time, area, and release status on survival, and we tested whether dispersal patterns among release areas were consistent with habitat selection theories. Results indicated that the survival of released adults was reduced during the first year after release, with no difference between sexes. Taking into account local observations only, we found that early survival rates varied across sites. However when we distinguished dispersal from mortality, early survival rates became equal across release sites. It thus appears that among reintroduction programs difference in failure and success was due to differential dispersal among release sites. We revealed asymmetrical patterns of dispersal due to conspecific attraction: dispersers selected the closest and the largest population. We showed that mortality can be homogeneous from one program to another while, on the contrary, dispersal is highly dependent on the matrix of established populations. Dispersal behavior is thus of major interest for metapopulation restoration and should be taken into account in planning reintroduction designs.     

Forecasting the number of soil samples required to reduce remediation cost uncertainty

Sampling scheme design is an important step in the management of polluted sites. It largely controls the accuracy of remediation cost estimates. In practice, however, sampling is seldom designed to comply with a given level of remediation cost uncertainty. In this paper, we present a new technique that allows one to estimate of the number of samples that should be taken at a given stage of investigation to reach a forecasted level of accuracy. The uncertainty is expressed both in terms of volume of polluted soil and overall cost of remediation. This technique provides a flexible tool for decision makers to define the amount of investigation worth conducting from an environmental and financial perspective. The technique is based on nonlinear geostatistics (conditional simulations) to estimate the volume of soil that requires remediation and excavation and on a function allowing estimation of the total cost of remediation (including investigations). The geostatistical estimation accounts for support effect, information effect, and sampling errors. The cost calculation includes mainly investigation, excavation, remediation, and transportation. The application of the technique on a former smelting work site (lead pollution) demonstrates how the tool can be used. In this example, the forecasted volumetric uncertainty decreases rapidly for a relatively small number of samples (20-50) and then reaches a plateau (after 100 samples). The uncertainty related to the total remediation cost decreases while the expected total cost increases. Based on these forecasts, we show how a risk-prone decision maker would probably decide to take 50 additional samples while a risk-averse decision maker would take 100 samples.