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.     

A summer heat wave decreases the immunocompetence of the mesograzer, Idotea baltica

Extreme events associated with global change will impose increasing stress on coastal organisms. How strong biological interactions such as the host–parasite arms-race are modulated by environmental change is largely unknown. The immune system of invertebrates, in particular phagocytosis and phenoloxidase activity response are key defence mechanisms against parasites, yet they may be sensitive to environmental perturbations. We here simulated an extreme event that mimicked the European heat wave in 2003 to investigate the effect of environmental change on the immunocompetence of the mesograzer Idotea baltica. Unlike earlier studies, our experiment aimed at simulation of the natural situation as closely as possible by using long acclimation, a slow increase in temperature and a natural community setting including the animals’ providence with natural food sources (Zostera marina and Fucus vesiculosus). Our results demonstrate that a simulated heat wave results in decreased immunocompetence of the mesograzer Idotea baltica, in particular a drop of phagocytosis by 50%. This suggests that global change has the potential to significantly affect host–parasite interactions.     

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.     

Thorium and uranium contents in human urine: influence of age and residential area

Inductively coupled plasma mass spectrometry (ICP-MS) has been used for the determination of (232)Th and (238)U in urine of unexposed Jordanian subjects living in six cities. The range of (232)Th excretion in all subjects was found to be 1.4-640 microBq d(-1) with an average of 34.8 microBq d(-1) (geometric mean 15.8 microBq d(-1)). Results showed no statistically significant correlation with age and residential area. The average value obtained is in agreement with levels considered normal in some recent publications. The average value of (238)U in all samples was found to be 3955 microBq d(-1) (geometric mean 1107 microBq d(-1)), which is higher than reported figures from Germany and India, but in agreement with those figures given in ICRP publication, number 23. The mean values of the different groups were found to be proportional to age up to 60 years. A noticeable drop is observed for subjects greater than 60 years old.     

The role of door orientation on occupant injury in a nearside impact: a CIREN, MADYMO modeling and experimental study

OBJECTIVE: This study addressed the effects of vehicle height mismatch in side impact crashes. A light truck or SUV tends to strike the door of a passenger car higher causing the upper border to lead into the occupant space. Conversely, an impact centered lower on the door, from a passenger car, causes the lower border to lead. We proposed the hypothesis that the type of injury sustained by the occupant could be related to door orientation during its intrusion into the passenger compartment. METHOD: Data on door orientation and nearside occupant injuries were collected from 125 side impact crashes reported in the CIREN database. Experimental testing was performed using a pendulum carrying a frame and a vehicle door, impacting against a USDOT SID. The frame allowed the door orientation to be changed. A model was developed in MADYMO (v 6.2) using the more biofidelic dummies, BIOSID, and SIDIIs as well as USDOT SID. RESULTS: In side impact crashes with the lower border of the door leading, 81% of occupants sustained pelvic injury, 42% suffered rib fractures, and the rate of organ injury was 0.84. With the upper border leading, 46% of occupants sustained pelvic injury, 71% sustained rib fracture, and the rate of organ injuries per case increased to 1.13. The differences in the groups with respect to pelvic injury were significant at p = 0.01, rib fracture, p = 0.10, and organ injury, p = 0.001. Experimental testing showed that when the door angle changed from lower to upper border leading, peak T4 acceleration increased by 273% and pelvic acceleration decreased by 44%. The model demonstrated that when the door angle changed from lower to upper border leading, the USDOT SID showed a 29% increase in T4 acceleration and a 57% decrease in pelvic acceleration. The BIOSID dummy demonstrated a 36% increase in T1 acceleration, a 44% increase in abdominal rib 1 deflection, a 91% increase in thoracic rib 1 deflection, and a 33% decrease in pelvic acceleration. CONCLUSIONS: These data add more insight to the problem of mismatch during side impacts, where the bumper of the striking vehicle overrides the door beam, causing the upper part of the door to lead the intrusion into the passenger compartment. Even with the same delta V and intrusion, with the upper border of the door leading, more severe chest and organ injuries resulted. This data suggests that door orientation should be considered when testing subsystems for side impact protection.