Evaluating the sampling pattern when detecting Zones of Abrupt Change

We present a method for detecting the zones where an irregularly sampled variable changes abruptly in the plane. Such zones are called Zones of Abrupt Change (ZACs). This method not only allows estimation of ZACs, but also testing of their statistical significance against the null hypothesis of a stationary correlated random field. The sampling pattern, in particular its local density, is crucial in the detection of potential ZACs. In this paper, we address the problem of evaluating the sampling pattern by assessing the power of the local test used for detecting ZACs. It is shown that mapping the power allows us to identify zones where ZACs may or may not be detected. The methodology is applied to a soil data set sampled at eight different dates in an agricultural field. Detecting ZACs for the soil water content allowed us to identify permanent structures in the agricultural field related to the boundaries between different soil types. Mapping the power for various sampling densities proved to be useful to determine the minimal sampling density necessary for detecting ZACs.

Data assimilation for short range atmospheric dispersion of radionuclides: a case study of second-order sensitivity

This article presents the application of variational data assimilation to a simple Gaussian plume model for radionuclides. Adjoint modeling is applied to the model in order to minimize discrepancies between contamination observations and model outputs. The interest of such an approach is to get a better estimation of some parameters such as emissions or dispersion parameters. A second-order analysis is also performed to assess the sensitivity of the optimized parameters to some poorly known parameters. Sensitivity with respect to network design is also done.     

Spatial interpolation of air temperature using environmental context: Application to a crop model

The air temperature is one of the main input data in models for water balance monitoring or crop models for yield prediction. The different phenological stages of plant growth are generally defined according to cumulated air temperature from the sowing date. When these crop models are used at the regional scale, the meteorological stations providing input climatic data are not spatially dense enough or in a similar environment to reflect the crop local climate. Hence spatial interpolation methods must be used. Climatic data, particularly air temperature, are influenced by local environment. Measurements show that the air above dry surfaces is warmer than above wet areas. We propose a method taking into account the environment of the meteorological stations in order to improve spatial interpolation of air temperature. The aim of this study is to assess the impact of these corrected climatic data in crop models. The proposed method is an external drift kriging where the Kriging system is modified to correct local environment effects. The environment of the meteorological stations was characterized using a land use map summarized in a small number of classes considered as a factor influencing local temperature. This method was applied to a region in south-east France (150×250 km) where daily temperatures were measured on 150 weather stations for two years. Environment classes were extracted from the CORINE Landcover map obtained from remote sensing data. Categorical external drift kriging was compared to ordinary kriging by a cross validation study. The gain in precision was assessed for different environment classes and for summer days. We then performed a sensitivity study of air temperature with the crop model STICS. The influence of interpolation corrections on the main outputs as yield or harvest date is discussed. We showed that the method works well for air temperature in summer and can lead to significant correction for yield prediction. For example, we observed by cross validation a bias reduction of 0.5 to 1.0°C (exceptionally 2.5°C for some class), which corresponds to differences in yield prediction from 0.6 to 1.5 t/ha.     

Cold winter temperatures condition the egg-hatching dynamics of a grape disease vector

The leafhopper Scaphoideus titanus is the vector of a major phytoplasma grapevine disease, Flavescence dorée. The vector’s distribution is in Eastern and Northern Europe, and its population dynamics varies as a function of vineyard latitude. We tested the hypothesis that hatching dynamics are cued by cold temperatures observed in winter. We exposed eggs from a natural population to simulated “cold” and “mild” winters and varied the exposure time at 5 °C from 0 to 63 days. We show that temperature cooling mainly affected the onset of hatching and is negatively correlated to the cold time exposure. The majority of hatchings occurred more quickly in cold rather than in mild winter simulated conditions, but there was no significant difference between the duration of hatching of eggs whatever the cold time exposure. In agreement with the Northern American origin of the vector, the diapause termination and thus the timing regulation of egg hatching require cold winters.     

Anticipation and tracking of pulsed resources drive population dynamics in eastern chipmunks

Pulsed systems are characterized by boom and bust cycles of resource production that are expected to cascade through multiple trophic levels. Many of the consumers within pulsed resource systems have specific adaptations to cope with these cycles that may serve to either amplify or dampen their community-wide consequences. We monitored a seed predator, the eastern chipmunk (Tamias striatus), in an American beech (Fagus grandifolia) dominated forest, and used capture-mark-recapture analyses to estimate chipmunk vital rates and relate them to interannual variation in beech seed production. The summer activity and reproduction of adults anticipated autumn beech production, with high activity and intense reproduction occurring in summers prior to beech masts. Chipmunks also reproduced every spring following a beech mast. However, adult survival was independent of beech production. In contrast, juvenile survival was lower in years of mast failure than in years of mast production, but their activity was consistently high and independent of beech production. Population growth was strongly affected by the number of juveniles and therefore by beech seed production, which explains nearly 70% of variation in population growth. Our results suggest that a combination of resource-dependent reproduction and variable activity levels associated with anticipation and response to resource pulses allows consumers to buffer potential deleterious effects of low food abundance on their survival.     

Etiology of fatal thoracic aortic injuries: Secondary data analysis

Objectives: Motor vehicle crashes remain a leading cause of death in the United States (US). Thoracic aortic dissection due to blunt trauma remains a major injury mechanism, and up to 90% of these injuries result in death on the scene. The objective of this study is to understand the modern risk factors and etiology of fatal thoracic aortic injuries in the current US fleet.

Methods: Using a unique, linked, Fatality Analysis Reporting System (FARS) and Multiple Cause of Death (MCOD) database from 2000–2010, 144,169 drivers over 16 years of age who suffered fatal injuries were identified. The merged database provides an unparalleled fidelity for identifying thoracic aortic injuries due to motor vehicle accidents. Thoracic aortic injuries were defined by ICD-10 codes S250. Univariate and multivariate logistic regression models for presence of any thoracic aortic injuries were fitted. Age, gender, BMI weight categories, vehicle class, model year, crash type/direction, severity of crash damage, airbag deployment location, and seatbelt use, fatal injury codes, and location of injury were considered. Odds ratios (OR) and corresponding 95% confidence intervals (95%CI) are calculated.

Results: There were 2953 deaths (2.10%) related to thoracic aortic injuries that met the inclusion criteria. Nearside crashes were associated with an increased odds (OR = 1.42, 1.1-1.83), while rollover crashes (OR =.44,.29-.66) were associated with a reduced odds of fatal thoracic aortic injury. Using backward selection on the full multivariate model, the only significant model effects that remained were vehicle type, crash type, body region, and injury type.

Conclusions: The increased prevalence of fatal thoracic aortic injury in nearside crashes, increasing age, and vehicle type provide some insight into the current US fleet. Important factors, including model year, had significantly lower levels of the injury in univariate analysis, demonstrating the effect of safety improvements in newer model vehicles. Further study of this fatal injury is warranted, including comparisons of those who survive the injury.     

Selectivity of Nano Zerovalent Iron in In Situ Chemical Reduction: Challenges and Improvements

Nano zerovalent iron (nZVI) is a promising remediation technology utilizing in situ chemical reduction (ISCR) to clean up contaminated groundwater at hazardous waste sites. The small particle size and large surface area of nZVI result in high reactivity and rapid destruction of contaminants. Over the past 20 years, a great deal of research has advanced the nZVI technology from bench‐scale tests to field‐scale applications. However, to date, the overall number of well‐characterized nZVI field deployments is still small compared to other alternative remedies that are more widely applied. Apart from the relatively high material cost of nZVI and questions regarding possible nanotoxicological side effects, one of the major obstacles to the widespread utilization of nZVI in the field is its short persistence in the environment due to natural reductant demand (NRD). The NRD for nZVI is predominantly due to reduction of water, but other reactions with naturally present oxidants (e.g., oxygen) occur, resulting in situ conditions that are reducing (high in ferrous iron phases and H₂) but with little or no Fe(0). This article reviews the main biogeochemical processes that determine the selectivity and longevity of nZVI, summarizes data from prior (laboratory and field) studies on the longevity of various common types of nZVI, and describes modifications of nZVI that could improve its selectivity and longevity for full‐scale applications of ISCR. © 2016 Wiley Periodicals, Inc.     

Rapid assessment of insect pollination services to inform decision-making

Pollinator declines have prompted efforts to assess how land-use change affects insect pollinators and pollination services in agricultural landscapes. Yet many tools to measure insect pollination services require substantial landscape-scale data and technical expertise. In expert workshops, 3 straightforward methods (desk-based method, field survey, and empirical manipulation with exclusion experiments) for rapid insect pollination assessment at site scale were developed to provide an adaptable framework that is accessible to nonspecialist with limited resources. These methods were designed for TESSA (Toolkit for Ecosystem Service Site-Based Assessment) and allow comparative assessment of pollination services at a site of conservation interest and in its most plausible alternative state (e.g., converted to agricultural land). We applied the methods at a nature reserve in the United Kingdom to estimate the value of insect pollination services provided by the reserve. The economic value of pollination services provided by the reserve ranged from US$6163 to US$11,546/year. The conversion of the reserve to arable land would provide no insect pollination services and a net annual benefit from insect-pollinated crop production of approximately $1542/year (US$24∙ha^–1∙year^–1). The methods had wide applicability and were readily adapted to different insect-pollinated crops: rape (Brassica napus) and beans (Vicia faba) crops. All methods were rapidly employed under a low budget. The relatively less robust methods that required fewer resources yielded higher estimates of annual insect pollination benefit.