Reducing the risk of invasive forest pests and pathogens: Combining legislation,targeted management and public awareness

Intensifying global trade will result in increased numbers of plant pest and pathogen species inadvertently being transported along with cargo. This paper examines current mechanisms for prevention and management of potential introductions of forest insect pests and pathogens in the European Union (EU). Current European legislation has not been found sufficient in preventing invasion, establishment and spread of pest and pathogen species within the EU. Costs associated with future invasions are difficult to estimate but past invasions have led to negative economic impacts in the invaded country. The challenge is combining free trade and free movement of products (within the EU) with protection against invasive pests and pathogens. Public awareness may mobilise the public for prevention and detection of potential invasions and, simultaneously, increase support for eradication and control measures. We recommend focus on commodities in addition to pathways, an approach within the EU using a centralised response unit and, critically, to engage the general public in the battle against establishment and spread of these harmful pests and pathogens.     

Benchmarking Optical/Thermal Satellite Imagery for Estimating Evapotranspiration and Soil Moisture in Decision Support Tools

Generally, one expects evapotranspiration (ET) maps derived from optical/thermal Landsat and MODIS satellite imagery to improve decision support tools and lead to superior decisions regarding water resources management. However, there is lack of supportive evidence to accept or reject this expectation. We “benchmark” three existing hydrologic decision support tools with the following benchmarks: annual ET for the ET Toolbox developed by the United States Bureau of Reclamation, predicted rainfall‐runoff hydrographs for the Gridded Surface/Subsurface Hydrologic Analysis model developed by the U.S. Army Corps of Engineers, and the average annual groundwater recharge for the Distributed Parameter Watershed Model used by Daniel B. Stephens & Associates. The conclusion of this benchmark study is that the use of NASA/USGS optical/thermal satellite imagery can considerably improve hydrologic decision support tools compared to their traditional implementations. The benefits of improved decision making, resulting from more accurate results of hydrologic support systems using optical/thermal satellite imagery, should substantially exceed the costs for acquiring such imagery and implementing the remote sensing algorithms. In fact, the value of reduced error in estimating average annual groundwater recharge in the San Gabriel Mountains, California alone, in terms of value of water, may be as large as $1 billion, more than sufficient to pay for one new Landsat satellite.     

Cropland changes in times of conflict,reconstruction, and economic development in Iraqi Kurdistan

The destruction of land and forced migration during the Anfal attacks against the Kurds in Iraq in the late 1980s has been reported to have severe consequences for agricultural development. A reconstruction program to aid people in returning to their lands was launched in 1991. To assess the agricultural situation in the Duhok governorate during the pre-Anfal (A), post-Anfal (B), reconstruction (C), and present (D) periods, we mapped winter crops by focusing on inter-annual variability in vegetation greenness, using satellite images. The results indicate a decrease in cultivated area between period A and B, and a small increase between period B and C. This supports reports of a decline in cultivated area related to the Anfal campaign, and indicates increased activity during the reconstruction program. Period D showed a potential recovery with a cropland area similar to period A.     

Selecting optimal hyperspectral bands to discriminate nitrogen status in durum wheat: a comparison of statistical approaches

Hyperspectral data can provide prediction of physical and chemical vegetation properties, but data handling, analysis, and interpretation still limit their use. In this study, different methods for selecting variables were compared for the analysis of on-the-ground hyperspectral signatures of wheat grown under a wide range of nitrogen supplies. Spectral signatures were recorded at the end of stem elongation, booting, and heading stages in 100 georeferenced locations, using a 512-channel portable spectroradiometer operating in the 325–1075-nm range. The following procedures were compared: (i) a heuristic combined approach including lambda-lambda R² (LL R²) model, principal component analysis (PCA), and stepwise discriminant analysis (SDA); (ii) variable importance for projection (VIP) statistics derived from partial least square (PLS) regression (PLS-VIP); and (iii) multiple linear regression (MLR) analysis through maximum R-square improvement (MAXR) and stepwise algorithms. The discriminating capability of selected wavelengths was evaluated by canonical discriminant analysis. Leaf-nitrogen concentration was quantified on samples collected at the same locations and dates and used as response variable in regressive methods. The different methods resulted in differences in the number and position of the selected wavebands. Bands extracted through regressive methods were mostly related to response variable, as shown by the importance of the visible region for PLS and stepwise. Band selection techniques can be extremely useful not only to improve the power of predictive models but also for data interpretation or sensor design.     

Bibliometric analysis of simulated driving research from 1997 to 2016

Objective: The objective of this study was to explore the evolution footprints of simulated driving research in the past 20 years through rigorous and systematic bibliometric analysis, to provide insights regarding when and where the research was performed and by whom and how the mainstream content evolved over the years.

Methods: The analysis began with data retrieval in Web of Science with defined search terms related to simulated driving. BibExcel and CiteSpace were employed to conduct the performance analysis and co-citation network analysis; that is, probe of the performance of institutes, journals, authors, and research hotspots.

Results: A total of 3,766 documents were filtered out and presented an exponential growth from 1997 to 2016. The United States contributed the most publications as well as international collaborations followed by Germany and China. In addition, several universities in The Netherlands and the United States dominated the list of contributing institutes. The leading journals were in transportation and ergonomics. The leading researchers were also recognized among the 8,721 contributing authors, such as J. D. Lee, D. L. Fisher, J. H. Kim, and K. A. Brookhuis. Finally, the co-citation analysis illuminated the evolution of simulated driving research that covered the following topics roughly in chronological order: task-induced stress, drivers with neurological disorders, alertness and sleepiness while driving, trust toward driving assistance systems, driver distraction, the effect of drug use, the validity of simulators, and automated driving.

Conclusions: This article employed bibliometric tools to probe the contributing countries, institutes, journals, authors, and mainstream hotspots of simulated driving research in the past 20 years. A systematic bibliometric analysis of this field will help researchers realize the panorama of global simulated driving and establish future research directions.     

Production and optimization of biodiesel using mixed immobilized biocatalysts in packed bed reactor

Vegetable oils are used as raw materials for biodiesel production using transesterification reaction. Several methods for the production of biodiesel were developed using chemical (alkali and acidic compounds) and biological catalysts (lipases). Biodiesel production catalyzed by lipases is energy and cost-saving processes and is carried out at normal temperature and pressure. The need for an efficient method for screening larger number of variables has led to the adoption of statistical experimental design. In the present study, packed bed reactor was designed to study with mixed immobilized biocatalysts to have higher productivity under optimum conditions. Contrary to the single-step acyl migration mechanism, a two-step stepwise reaction mechanism involving immobilized Candida rugosa lipase and immobilized Rhizopus oryzae cells was employed for the present work. This method was chosen because enzymatic hydrolysis followed by esterification can tolerate high free fatty acid containing oils. The effects of flow rate and bed height on biodiesel yield were studied using two factors five-level central composite design (CCD) and response surface methodology (RSM). Maximum biodiesel yield of 85 and 81 % was obtained for jatropha oil and karanja oil with the optimum bed height and optimum flow rate of 32.6 cm and 1.35 L/h, and 32.6 cm and 1.36 L/h, respectively.     

Does social justice knowledge matter? Education for sustainable development and student attitudes

Recent conjecture on the potential primacy of physical environmental components in education for sustainable development (ESD) efforts serves to question the centrality of social justice education as a component of ESD. This research explores a sustainable development student’s basic knowledge of social justice conditions in their country of residence and its relationships to policy attitudes that should be of importance to ESD, including beliefs about the importance of corporate social responsibility, their endorsement of gross national product as an effective measure of progress, their overall assessment of the social fairness of current national social justice policy, and their endorsement of the goals of Occupy Wall Street. Results obtained using path-model hypothesis testing indicate that accuracy of knowledge of US standing on social justice issues is significantly related to these policy attitudes, providing support for social justice content in ESD endeavors to create students empowered for engagement in broader policy goals.     

Augmenting Watershed Model Calibration with Incorporation of Ancillary Data Sources and Qualitative Soft Data Sources

Watershed simulation models such as the Soil & Water Assessment Tool (SWAT) can be calibrated using “hard data” such as temporal streamflow observations; however, users may find upon examination of model outputs, that the calibrated models may not reflect actual watershed behavior. Thus, it is often advantageous to use “soft data” (i.e., qualitative knowledge such as expected denitrification rates that observed time series do not typically exist) to ensure that the calibrated model is representative of the real world. The primary objective of this study is to evaluate the efficacy of coupling SWAT‐Check (a post‐evaluation framework for SWAT outputs) and IPEAT‐SD (Integrated Parameter Estimation and Uncertainty Analysis Tool‐Soft & hard Data evaluation) to constrain the bounds of soft data during SWAT auto‐calibration. IPEAT‐SD integrates 59 soft data variables to ensure SWAT does not violate physical processes known to occur in watersheds. IPEAT‐SD was evaluated for two case studies where soft data such as denitrification rate, nitrate attributed from subsurface flow to total discharge ratio, and total sediment loading were used to conduct model calibration. Results indicated that SWAT model outputs may not satisfy reasonable soft data responses without providing pre‐defined bounds. IPEAT‐SD provides an efficient and rigorous framework for users to conduct future studies while considering both soft data and traditional hard information measures in watershed modeling.     

Hydroponic root mats for wastewater treatment—a review

Hydroponic root mats (HRMs) are ecotechnological wastewater treatment systems where aquatic vegetation forms buoyant filters by their dense interwoven roots and rhizomes, sometimes supported by rafts or other floating materials. A preferential hydraulic flow is created in the water zone between the plant root mat and the bottom of the treatment system. When the mat touches the bottom of the water body, such systems can also function as HRM filter; i.e. the hydraulic flow passes directly through the root zone. HRMs have been used for the treatment of various types of polluted water, including domestic wastewater; agricultural effluents; and polluted river, lake, stormwater and groundwater and even acid mine drainage. This article provides an overview on the concept of applying floating HRM and non-floating HRM filters for wastewater treatment. Exemplary performance data are presented, and the advantages and disadvantages of this technology are discussed in comparison to those of ponds, free-floating plant and soil-based constructed wetlands. Finally, suggestions are provided on the preferred scope of application of HRMs.