Carrier screening for cystic fibrosis

A number of different models of CF carrier screening have now been tested in pilot trials. Apart from opportunistic and cascade testing (which are strictly speaking not true forms of screening), the major programmes have been directed either to young adults in primary care or to pregnant women in antenatal clinics. Only in the latter form of screening has sufficient data been collected to allow conclusions to be reached on the optimum mode of delivery. It seems very probable that when CF carrier screening passes into routine service, it will be the antenatal couple model that is used.     

中国东南沿海大(中)型浅成中低温热液矿床—斑岩型矿床评价的地质准则、成矿模式及其找矿意义

本文总结中国东南沿海高钾钙碱性—双峰式火山岩带中已勘查大中型矿床成矿环境的共性：矿床所处区域构造的部位、成岩与成矿时代、矿床与岩浆成因类型、火山构造及其基底构造控矿性、矿床与爆发角砾岩、矿床与矿化类型叠加与共生、矿化与蚀变的分带往、矿床定位深度与剥蚀深度。作者认为这八点可作为找寻与评价大（中）型矿床的地质准则。通过火山地质与矿床地质统一的研究提出本区晚中生代以火山为中心地热体系的成矿模式。并就三个方面作类比：①与现代火山地热体系成矿作用类比；②以紫金山高硫型浅成低温热液矿床与世界同类型矿床作比较；③与环太平洋其他火山岩带同类型矿床模式作类比．通过建立本区的模式与类比获得进一步找矿中值得重视的一些思路．     

Uncertainty Models for Estimates of Physical Characteristics of River Segments Over Large Areas

Spatially comprehensive estimates of the physical characteristics of river segments over large areas are required in many large‐scale analyses of river systems and for the management of multiple basins. Remote sensing and modeling are often used to estimate river characteristics over large areas, but the uncertainties associated with these estimates and their dependence on the physical characteristics of the segments and their catchments are seldom quantified. Using test data with varying degrees of independence, we derived analytical models of the uncertainty associated with estimates of upstream catchment area (CA), segment slope, and mean annual discharge for all river segments of a digital representation of the hydrographic network of France. Although there were strong relationships between our test data and estimates at the scale of France, there were also large relative local uncertainties, which varied with the physical characteristics of the segments and their catchments. Discharge and CA were relatively uncertain where discharge was low and catchments were small. Discharge uncertainty also increased in catchments with large rainfall events and low minimum temperature. The uncertainty of segment slope was strongly related to segment length. Our uncertainty models were consistent across large regions of France, suggesting some degree of generality. Their analytical formulation should facilitate their use in large‐scale ecological studies and simulation models.     

A Recourse‐Based Interval Fuzzy Programming Model for Point‐Nonpoint Source Effluent Trading under Uncertainty

In this study, a recourse‐based interval fuzzy programming (RIFP) model is developed for tackling uncertainties expressed as fuzzy, interval, and/or probabilistic forms in an effluent trading program. It can incorporate preregulated water‐pollution control policies directly into its optimization process, such that an effective linkage between environmental regulations and economic implications (i.e., penalties) caused by improper policies due to uncertainty existence can be provided. The RIFP model is applied to point‐nonpoint source effluent trading of the Xiangxi River in China. The efficiency of trading efforts between water quality improvement and net system benefit under different degrees of satisfying discharge limits is analyzed. The results are able to help support (1) formulation of water‐pollution control strategies under various economic objectives and system‐reliability constraints, (2) selection of the desired effluent trading pattern for point and nonpoint sources, and (3) generation of tradeoffs among system benefit, satisfaction degree, and pollutant mitigation under multiple uncertainties. Compared with the traditional regulatory approaches, the results demonstrate that the water‐pollution control program can be performed more cost‐effectively through trading than nontrading.     

Sustainable Land Management (SLM) Practices in Drylands: How Do They Address Desertification Threats?

Managing land sustainably is a huge challenge, especially under harsh climatic conditions such as those found in drylands. The socio-economic situation can also pose challenges, as dryland regions are often characterized by remoteness, marginality, low-productive farming, weak institutions, and even conflict. With threats from climate change, disputes over water, competing claims on land, and migration increasing worldwide, the demands for sustainable land management (SLM) measures will only increase in the future. Within the EU-funded DESIRE project, researchers and stakeholders jointly identified existing SLM technologies and approaches in 17 dryland study sites located in the Mediterranean and around the world. In order to evaluate and share this valuable SLM experience, local researchers documented the SLM technologies and approaches in collaboration with land users, utilizing the internationally recognized WOCAT questionnaires. This article provides an analysis of 30 technologies and 8 approaches, enabling an initial evaluation of how SLM addresses prevalent dryland threats, such as water scarcity, soil degradation, vegetation degradation and low production, climate change, resource use conflicts, and migration. Among the impacts attributed to the documented technologies, those mentioned most were diversified and enhanced production and better management of water and soil degradation, whether through water harvesting, improving soil moisture, or reducing runoff. Favorable local-scale cost–benefit relationships were mainly found when considered over the long term. Nevertheless, SLM was found to improve people’s livelihoods and prevent further outmigration. More field research is needed to reinforce expert assessments of SLM impacts and provide the necessary evidence-based rationale for investing in SLM.     

An Ecology of Prestige in New York City: Examining the Relationships Among Population Density,Socio-economic Status,Group Identity,and Residential Canopy Cover

Several social theories have been proposed to explain the uneven distribution of vegetation in urban residential areas: population density, social stratification, luxury effect, and ecology of prestige. We evaluate these theories using a combination of demographic and socio-economic predictors of vegetative cover on all residential lands in New York City. We use diverse data sources including the City’s property database, time-series demographic and socio-economic data from the US Census, and land cover data from the University of Vermont’s Spatial Analysis Lab (SAL). These data are analyzed using a multi-model inferential, spatial econometrics approach. We also examine the distribution of vegetation within distinct market categories using Claritas’ Potential Rating Index for Zipcode Markets (PRIZM?) database. These categories can be disaggregated, corresponding to the four social theories. We compare the econometric and categorical results for validation. Models associated with ecology of prestige theory are more effective for predicting the distribution of vegetation. This suggests that private, residential patterns of vegetation, reflecting the consumption of environmentally relevant goods and services, are associated with different lifestyles and lifestages. Further, our spatial and temporal analyses suggest that there are significant spatial and temporal dependencies that have theoretical and methodological implications for understanding urban ecological systems. These findings may have policy implications. Decision makers may need to consider how to most effectively reach different social groups in terms of messages and messengers in order to advance land management practices and achieve urban sustainability.