Genetically Modified (GM) Crops: Precautionary Science and Conflicts of Interests

Risk governance of GM plants and GMfood products is presently subject to heatedscientific and public controversies. Scientistsand representatives of the biotechnologyindustry have dominated debates concerningsafety issues. The public is suspicious withregard to the motives of scientists, companies,and political institutions involved. Thedilemmas posed are nested, embracing valuequestions, scientific uncertainty, andcontextual issues. The obvious lack of data andinsufficient information concerning ecologicaleffects call for application of thePrecautionary Principle (PP). There are,however, divergent opinions among scientistsabout the relevance of putative hazards,definition of potential ``adverse effects,' andwhether actions should be taken to preventharm. The reliance on the concept ofsubstantial equivalence in safety evaluation ofGM food is equally controversial. Consequently,value assumptions embedded in a scientificframework may be a barrier for employment ofthe PP. One of our major conclusions is thatprecautionary GMP usage requires riskassessment criteria yet undeveloped, as well asbroader and more long-term conceptions of risk,uncertainty, and ignorance. Conflicts ofinterest and public participation are otherissues that need to be taken intoconsideration. GMP governance regimes that arejustifiable from a precautionary and ethicalpoint of view must transcend traditionalscientific boundaries to include alternativescientific perspectives as well as publicinvolvement.     

METHODOLOGIES FOR CALIBRATION AND PREDICTIVE ANALYSIS OF A WATERSHED MODEL1

ABSTRACT: The use of a fitted parameter watershed model to address water quantity and quality management issues requires that it be calibrated under a wide range of hydrologic conditions. However, rarely does model calibration result in a unique parameter set. Parameter nonuniqueness can lead to predictive nonuniqueness. The extent of model predictive uncertainty should be investigated if management decisions are to be based on model projections. Using models built for four neighboring watersheds in the Neuse River Basin of North Carolina, the application of the automated parameter optimization software PEST in conjunction with the Hydrologic Simulation Program Fortran (HSPF) is demonstrated. Parameter nonuniqueness is illustrated, and a method is presented for calculating many different sets of parameters, all of which acceptably calibrate a watershed model. A regularization methodology is discussed in which models for similar watersheds can be calibrated simultaneously. Using this method, parameter differences between watershed models can be minimized while maintaining fit between model outputs and field observations. In recognition of the fact that parameter nonuniqueness and predictive uncertainty are inherent to the modeling process, PEST's nonlinear predictive analysis functionality is then used to explore the extent of model predictive uncertainty.     

UNCERTAINTY IN ESTIMATING BANKFULL CONDITIONS1

ABSTRACT: Bankfull depth and discharge are basic input parameters to stream planform, stream restoration, and highway crossing designs, as well as to the development of hydraulic geometry relationships and the classification of streams. Unfortunately, there are a wide variety of definitions for bankfull that provide a range of values, and the actual selection of bankfull is subjective. In this paper, the relative uncertainty in determining the bankfull depth and discharge is quantified, first by examining the variability in the estimates of bankfull and second by using fuzzy numbers to describe bankfull depth. Fuzzy numbers are used to incorporate uncertainty due to vagueness in the definition of bankfull and subjectivity in the selection of bankfull. Examples are provided that demonstrate the use of a fuzzy bankfull depth in sediment trans. port and in stream classification. Using fuzzy numbers to describe bankfull depth rather than a deterministic value allows the engineer to base designs and decisions on a range of possible values and associated degrees of belief that the bankfull depths take on each value in that range.     

二级处理后的城市污水用作电厂冷却水若干问题的探讨

介绍了二级处理后的城市污水（TSE）用作电厂开式循环冷却水时，由于城市污水中氨氮、微生物及菌类含量较高，可能给循环水系统带来的危害，并探讨了危害产生的原因及控制措施。     

城市中水回用于循环冷却水的氨氮去除试验研究

对氨氮浓度较高的城市中水回用于循环冷却水进行了静态和动态模拟试验，研究了氨氮在两种不同试验条件下的变化以及对系统产生的影响。试验结果表明：随着浓缩倍率的升高，循环水中氨氮浓度大幅度下降，大部分氨氮是由于冷却塔对氨的吹脱作用而被去除。试验过程中，氨氮浓度的降低没有导致系统的腐蚀。用氨氮浓度较高的城市中水回用于循环冷却水是可行的。     

综合防尘技术在煤矿的应用实践

粉尘严重威胁矿井安全生产和职工身体健康。公司依靠科学管理，完善了各项综合防尘管理制度，制定了一系列综合防尘方面的管理规定和防尘技术操作规程；加强技术创新，重点抓好综采、综掘工作面以及回风系统和定点尘源的装置，实行自动控制等综合防尘技术；从管理和技术创新角度，通过采用减少粉尘产生、降尘、排尘、除尘、个体防尘等综合防尘技术措施应用实践，取得了良好的效果。     

BSE in the UK: Why the Risk Communication Strategy Failed

The 2000 BSE Inquiry report points out that the most serious failure of the UK Government was one of risk communication. This paper argues that the government's failure to communicate the risks BSE posed to humans to a large degree can be traced back to a lack of transparency in the first risk assessment by the Southwood Working Party. This lack of transparency ensured that the working party's risk characterization and recommendations were ambiguous and thus hard to interpret. It also meant that uncertainties were not addressed in a satisfactory way. In the recommendations, the attitude to uncertainty was implicit rather than explicit.The risk communication based on the report amplified these flaws. Most importantly, it did not address the uncertainty at all. Apparently, the reason for this was fear of overreaction by the public. However, the result was counter-productive, because the risk communication did not then appear trustworthy. Later risk assessments and risk communication omitted to correct these flaws. Indeed, the fact that, following receipt of new information, advisory experts and policy makers had changed their views of the risk to humans was never clearly communicated to the public. There seemed to be little faith in the public's ability to reach a balanced judgment regarding the uncertainties.In the concluding section of the paper, this analysis is compared with the food standards agency's (FSA's) approach to BSE. The intervention of this agency was seen as one of the more important efforts to restore consumer confidence in British beef. And the agency certainly appears to be committed to openness and to addressing scientific uncertainty. However, using the risk of BSE in sheep as a case study, the paper shows that transparency – i.e., the clear presentation of factual and normative claims and assumptions underlying advice, and openness about the reasoning based on these claims and assumptions – is less than fully achieved in the FSA's work.     

Implications of different population model structures for management of threatened plants

Population viability analysis (PVA) is a reliable tool for ranking management options for a range of species despite parameter uncertainty. No one has yet investigated whether this holds true for model uncertainty for species with complex life histories and for responses to multiple threats. We tested whether a range of model structures yielded similar rankings of management and threat scenarios for 2 plant species with complex postfire responses. We examined 2 contrasting species from different plant functional types: an obligate seeding shrub and a facultative resprouting shrub. We exposed each to altered fire regimes and an additional, species‐specific threat. Long‐term demographic data sets were used to construct an individual‐based model (IBM), a complex stage‐based model, and a simple matrix model that subsumes all life stages into 2 or 3 stages. Agreement across models was good under some scenarios and poor under others. Results from the simple and complex matrix models were more similar to each other than to the IBM. Results were robust across models when dominant threats are considered but were less so for smaller effects. Robustness also broke down as the scenarios deviated from baseline conditions, likely the result of a number of factors related to the complexity of the species’ life history and how it was represented in a model. Although PVA can be an invaluable tool for integrating data and understanding species’ responses to threats and management strategies, this is best achieved in the context of decision support for adaptive management alongside multiple lines of evidence and expert critique of model construction and output.     

The difficulties of systematic reviews

The need for robust evidence to support conservation actions has driven the adoption of systematic approaches to research synthesis in ecology. However, applying systematic review to complex or open questions remains challenging, and this task is becoming more difficult as the quantity of scientific literature increases. We drew on the science of linguistics for guidance as to why the process of identifying and sorting information during systematic review remains so labor intensive, and to provide potential solutions. Several linguistic properties of peer‐reviewed corpora—including nonrandom selection of review topics, small‐world properties of semantic networks, and spatiotemporal variation in word meaning—greatly increase the effort needed to complete the systematic review process. Conversely, the resolution of these semantic complexities is a common motivation for narrative reviews, but this process is rarely enacted with the rigor applied during linguistic analysis. Therefore, linguistics provides a unifying framework for understanding some key challenges of systematic review and highlights 2 useful directions for future research. First, in cases where semantic complexity generates barriers to synthesis, ecologists should consider drawing on existing methods—such as natural language processing or the construction of research thesauri and ontologies—that provide tools for mapping and resolving that complexity. These tools could help individual researchers classify research material in a more robust manner and provide valuable guidance for future researchers on that topic. Second, a linguistic perspective highlights that scientific writing is a rich resource worthy of detailed study, an observation that can sometimes be lost during the search for data during systematic review or meta‐analysis. For example, mapping semantic networks can reveal redundancy and complementarity among scientific concepts, leading to new insights and research questions. Consequently, wider adoption of linguistic approaches may facilitate improved rigor and richness in research synthesis.     

Environmental cost of using poor decision metrics to prioritize environmental projects

Conservation decision makers commonly use project‐scoring metrics that are inconsistent with theory on optimal ranking of projects. As a result, there may often be a loss of environmental benefits. We estimated the magnitudes of these losses for various metrics that deviate from theory in ways that are common in practice. These metrics included cases where relevant variables were omitted from the benefits metric, project costs were omitted, and benefits were calculated using a faulty functional form. We estimated distributions of parameters from 129 environmental projects from Australia, New Zealand, and Italy for which detailed analyses had been completed previously. The cost of using poor prioritization metrics (in terms of lost environmental values) was often high—up to 80% in the scenarios we examined. The cost in percentage terms was greater when the budget was smaller. The most costly errors were omitting information about environmental values (up to 31% loss of environmental values), omitting project costs (up to 35% loss), omitting the effectiveness of management actions (up to 9% loss), and using a weighted‐additive decision metric for variables that should be multiplied (up to 23% loss). The latter 3 are errors that occur commonly in real‐world decision metrics, in combination often reducing potential benefits from conservation investments by 30–50%. Uncertainty about parameter values also reduced the benefits from investments in conservation projects but often not by as much as faulty prioritization metrics.