The use of statistical tools in field testing of putative effects of genetically modified plants on nontarget organisms

To fulfill existing guidelines, applicants that aim to place their genetically modified (GM) insect‐resistant crop plants on the market are required to provide data from field experiments that address the potential impacts of the GM plants on nontarget organisms (NTO's). Such data may be based on varied experimental designs. The recent EFSA guidance document for environmental risk assessment (2010) does not provide clear and structured suggestions that address the statistics of field trials on effects on NTO's. This review examines existing practices in GM plant field testing such as the way of randomization, replication, and pseudoreplication. Emphasis is placed on the importance of design features used for the field trials in which effects on NTO's are assessed. The importance of statistical power and the positive and negative aspects of various statistical models are discussed. Equivalence and difference testing are compared, and the importance of checking the distribution of experimental data is stressed to decide on the selection of the proper statistical model. While for continuous data (e.g., pH and temperature) classical statistical approaches – for example, analysis of variance (ANOVA) – are appropriate, for discontinuous data (counts) only generalized linear models (GLM) are shown to be efficient. There is no golden rule as to which statistical test is the most appropriate for any experimental situation. In particular, in experiments in which block designs are used and covariates play a role GLMs should be used. Generic advice is offered that will help in both the setting up of field testing and the interpretation and data analysis of the data obtained in this testing. The combination of decision trees and a checklist for field trials, which are provided, will help in the interpretation of the statistical analyses of field trials and to assess whether such analyses were correctly applied.     

基于遗传算法特征选择的HBV再激活分类预测模型

探讨原发性肝癌患者精确放疗后乙型肝炎病毒(hepatitis b virus,HBV)再激活的危险特征和分类预测模型。提出基于遗传算法的特征选择方法,从原发性肝癌数据的初始特征集中选择HBV再激活的最优特征子集。建立贝叶斯和支持向量机的HBV再激活分类预测模型,并预测最优特征子集和初始特征集的分类性能。实验结果表明,基于遗传算法的特征选择提高了HBV再激活分类性能,最优特征子集的分类性能明显优于初始特征子集的分类性能。影响HBV再激活的最优特征子集包括:HBV DNA水平,肿瘤分期TNM,Child-Pugh,外放边界和全肝最大剂量。贝叶斯的分类准确性最高可达82.89%,支持向量机的分类准确性最高可达83.34%。     

基于提高鸟类多样性的北京城市线性公园绿地植物景观探析

植被覆盖率高的线性公园,可作为鸟类的迁徙途径和栖息之所,并猜测其可作为生态廊道的一部分,适宜的营造植物景观、提升植物种类的多样性对保护鸟类多样性有促进作用。因此,采用标准取样法对北京城市线性公园绿地进行研究,提取可能影响鸟类多样性的植物群落因素、植物生境因素,对提高鸟类多样性提出建设性的意见。研究结果主要表明,在线性公园绿地宽度30~200m内,随着宽度的增加,鸟类的数量有所提高;含有不同类型植物生境的线性公园绿地,对鸟类目标种的吸引力不同,植物生境类型数较多样的线性公园绿地具有较高的鸟类目标种吸引力;不同的鸟类目标种偏好在不同的树种上进行活动。     

Bioarchaeological evidence for adaptive plasticity and constraint: Exploring life‐history trade‐offs in the human past

The Developmental Origins of Health and Disease paradigm evaluates the consequences of early life stress on health at later stages of life. Interacting with this paradigm represents a profound opportunity to leverage the lifespan and contextual approaches to human skeletal remains adopted by bioarchaeological research. Teeth and bone provide evidence for stressors experienced early in life. These events represent evidence for adaptive plasticity as Individuals survive the events through reallocation of energy to essential physiological functions, which inhibits enamel and skeletal growth. Age‐at‐death, adult body size, chronic infection, or childhood mortality may be used as covariates to better understand the physiological constraints operating on individual bodies following survival of early life stress. Contextual evidence from cemeteries provides clues to the ecological and cultural contingencies that exacerbate or mitigate the expression of these trade‐offs. Future studies should incorporate newly derived methods that provide reproducible and precise ways to evaluate early life stress, while incorporating populations that are often neglected.     

Towards Productive Cities: Environmental Assessment of the Food‐Energy‐Water Nexus of the Urban Roof Mosaic

Cities are rapidly growing and need to look for ways to optimize resource consumption. Metropolises are especially vulnerable in three main systems, often referred to as the FEW (i.e., food, energy, and water) nexus. In this context, urban rooftops are underutilized areas that might be used for the production of these resources. We developed the Roof Mosaic approach, which combines life cycle assessment with two rooftop guidelines, to analyze the technical feasibility and environmental implications of producing food and energy, and harvesting rainwater on rooftops through different combinations at different scales. To illustrate, we apply the Roof Mosaic approach to a densely populated neighborhood in a Mediterranean city. The building‐scale results show that integrating rainwater harvesting and food production would avoid relatively insignificant emissions (13.9–18.6 kg CO₂ eq/inhabitant/year) in the use stage, but their construction would have low environmental impacts. In contrast, the application of energy systems (photovoltaic or solar thermal systems) combined with rainwater harvesting could potentially avoid higher CO₂ eq emissions (177–196 kg CO₂ eq/inhabitant/year) but generate higher environmental burdens in the construction phase. When applied at the neighborhood scale, the approach can be optimized to meet between 7% and 50% of FEW demands and avoid up to 157 tons CO₂ eq/year. This approach is a useful guide to optimize the FEW nexus providing a range of options for the exploitation of rooftops at the local scale, which can aid cities in becoming self‐sufficient, optimizing resources, and reducing CO₂ eq emissions.     

Energy,Nitrogen, and Farm Surplus Transitions in Agriculture from Historical Data Modeling. France, 1882–2013.

This article addresses agricultural metabolism and transitions for energy, nitrogen, farm production, self‐sufficiency, and surplus from historical data since the nineteenth century. It builds on an empirical data set on agricultural production and production means in France covering 130 consecutive years (1882–2013). Agricultural transitions have increased the net production and surplus of farms by a factor of 4 and have zeroed self‐sufficiency. The energy consumption remained quasi‐stable since 1882, but the energy and nitrogen structure of agriculture fully changed. With an EROI (energy return to energy invested) of 2 until 1950, preindustrial agriculture consumed as much energy to function as it provided in exportable surplus to sustain the nonagricultural population. The EROI doubled to 4 over the last 60 years, driven, on the one hand, by efficiency improvements in traction through the replacement of draft animals by motors and, on the other hand, by the joint increase in crop yields and efficiency in nitrogen use. Agricultural energy and nitrogen transitions shifted France from a self‐sufficiency agri‐food‐energy regime to a fossil‐dependent food export regime. Knowledge of resource conversion mechanisms over the long duration highlights the effects of changing agricultural metabolism on the system's feeding capacity. Farm self‐sufficiency is an asset against fossil fuel constraints, price volatility, and greenhouse gas emissions, but it equates to lower farm surplus in support of urbanization.