国际河流管理合作模式的分类及演进规律探讨

论文对国际河流管理合作模式的概念、分类及演进规律进行了探讨。在从合作主体、目标、途径、制度等方面对合作模式进行单维度分类的基础上,借鉴霍尔三维结构图系统分析方法,构建了合作模式三维度分类模型,较全面、准确地概括了当前国际河流管理合作实践的模式类型。最后,综合世界各种典型国际河流管理合作模式的形成和发展过程,从模式要素的发展演变及模式演进的动力机制两个方面入手,详细阐述了国际河流管理合作模式的演进规律。     

Do voluntary pollution reduction programs (VPRs) spur or deter environmental innovation? Evidence from 33/50

We study whether a government-sponsored voluntary pollution reduction program (VPR) promotes or deters the development of new environmental technologies that yield future emission reduction benefits. Using a panel of 127 U.S. manufacturing industries defined by 3-digit SIC classifications over the 1989–2004 period, we estimate impacts of industry-level participation in the 33/50 program, a VPR initiated by government regulators in 1991, on industry-level rates of environmental patenting. We find that higher rates of 33/50 program participation are associated with significant reductions in the number of successful environmental patent applications five to nine years after the program ended.     

Combining heat-transfer and energy budget models to predict thermal stress in Mediterranean intertidal mussels

Recent studies have emphasised that organisms can experience physiological stress well within their geographic range limits. Developing methods for mechanistically predicting the presence, absence and physiological performance of organisms is therefore important because of the ongoing effects of climate change. In this study, we merged a biophysical–ecological (BE) model that estimates the aquatic (high tide) and aerial (low tide) body temperatures of Mytilus galloprovincialis with a Dynamic Energy Budget (DEB) model to predict growth, reproduction and mortality of this Mediterranean mussel in both intertidal and subtidal environments. Using weather and chlorophyll-a data from three Mediterranean sites along the Italian coasts, we show that predictions of sublethal and lethal (acute) stress can potentially explain the observed distribution (both presence and absence) of mussels in the intertidal and subtidal zones, and the maximum size of animals in the subtidal zones. Importantly, our results suggest that different mechanisms limit the intertidal distribution of mussels, and that these mechanisms do not follow a simple latitudinal gradient. At the northernmost site (Palermo), M. galloprovincialis appears to be excluded from the intertidal zone due to persistent exposure to lethal aerial temperatures, whereas at the southernmost sites (Porto Empedocle and Lampedusa) sublethal stress is the most important driver of mussel intertidal distribution. Our predictions provide a set of hypotheses for future work on the role of climate change in limiting intertidal distribution of mussels in the Mediterranean.     

Modelling cadmium bioaccumulation in Gammarus pulex by using experimental design approach

Recently, although dynamic approaches have been used increasingly to describe metal bioaccumulation in aquatic organisms, the validation of such laboratory-derived modelling is rarely assessed under environmental conditions. The present study aims to evaluate and verify statistical and mathematical models for the bioaccumulation of cadmium (Cd) and to evaluate the suitability of Gammarus pulex as a biomonitor for Cd. To optimise Cd²⁺ ion bioaccumulation conditions a Box–Behnken design was used and whether G. pulex can be used as an estimated tool to assess aquatic quality was investigated. A Box–Behnken experimental design combined with response surface modelling (RSM) was employed for Cd²⁺ bioaccumulation in G. pulex. Independent variables including temperature, contact time and Cd²⁺ ion concentration significance and their interactions were tested using analysis of variance. The selected variables’ optimum values were obtained by solving the quadratic regression model along with by analysing the response surface contour plots. Based on Box–Behnken design, the applied model is significant because model F-value and R² were obtained as 5121.49, 0.9998, respectively. Bioaccumulation of Cd amount was analysed using electrothermal atomic absorption spectrophotometer. The obtained data suggest that G. pulex can be evaluated as Cd biomonitor.     

Regression models for some solute distribution equilibria in the terrestrial environment

Sorption coefficients (K_p) of several organochlorine insecticides (OCs) in volcanic ash silt from Central Java are presented.

Selected experimental and estimated octanol‐water partition coefficient (P) values are used to study log‐log regressions with K_p data collected from the literature (PAHs, chlorophenols, phenylureas, chloro‐s‐triazines, carbamates and organophosphorus insecticides) and those of the OCs determined in the present study. Leaching distances and bioactivities in soil are correlated with the K_p values of the pesticides, and with the organic matter and the water content of the soil.     

A critique of the official report on the evacuation of the World Trade Center: continued doubts

This paper criticises the conclusions and the unanswered questions in the National Institute of Standards and Technology (NIST)'s official report on the evacuation of the World Trade Center in New York City, United States, on 11 September 2001. It reviews the extent to which the report disregards several conventional statistical methods and comments on the NIST's refusal to share the machine‐readable data file with the scientific community for replication and further analysis. Problems lie in the sampling methods employed, the treatment of missing data, the use of ordinary least squares (OLS) with binary dependent variables, the failure to document the scalability of the scales used, the lack of tests to check for constant error variance, and the absence of overall fit tests of the model. There are also conceptual and theoretical issues, such as the absence in the report of considerations of the influence of group‐level processes and their impact on the collective behaviour of evacuating collectivities.     

An integrated approach for predicting fates of reintroductions with demographic data from multiple populations

We devised a novel approach to model reintroduced populations whereby demographic data collected from multiple sites are integrated into a Bayesian hierarchical model. Integrating data from multiple reintroductions allows more precise population-growth projections to be made, especially for populations for which data are sparse, and allows projections that account for random site-to-site variation to be made before new reintroductions are attempted. We used data from reintroductions of the North Island Robin (Petroica longipes), an endemic New Zealand passerine, to 10 sites where non-native mammalian predators are controlled. A comparison of candidate models that we based on deviance information criterion showed that rat-tracking rate (an index of rat density) was a useful predictor of robin fecundity and adult female survival, that landscape connectivity and a binary measure of whether sites were on a peninsula were useful predictors of apparent juvenile survival (probably due to differential dispersal away from reintroduction sites), and that there was unexplained random variation among sites in all demographic rates. We used the two best supported models to estimate the finite rate of increase (λ) for populations at each of the 10 sites, and for a proposed reintroduction site, under different levels of rat control. Only three of the reintroduction sites had λ distributions completely >1 for either model. At two sites, λ was expected to be >1 if rat-tracking rates were <5%. At the other five reintroduction sites, λ was predicted to be close to 1, and it was unclear whether growth was expected. Predictions of λ for the proposed reintroduction site were less precise than for other sites because distributions incorporated the full range of site-to-site random variation in vital rates. Our methods can be applied to any species for which postrelease data on demographic rates are available and potentially can be extended to model multiple species simultaneously.     

Predicting species distributions from samples collected along roadsides

Predictive models of species distributions are typically developed with data collected along roads. Roadside sampling may provide a biased (nonrandom) sample; however, it is currently unknown whether roadside sampling limits the accuracy of predictions generated by species distribution models. We tested whether roadside sampling affects the accuracy of predictions generated by species distribution models by using a prospective sampling strategy designed specifically to address this issue. We built models from roadside data and validated model predictions at paired locations on unpaved roads and 200 m away from roads (off road), spatially and temporally independent from the data used for model building. We predicted species distributions of 15 bird species on the basis of point-count data from a landbird monitoring program in Montana and Idaho (U.S.A.). We used hierarchical occupancy models to account for imperfect detection. We expected predictions of species distributions derived from roadside-sampling data would be less accurate when validated with data from off-road sampling than when it was validated with data from roadside sampling and that model accuracy would be differentially affected by whether species were generalists, associated with edges, or associated with interior forest. Model performance measures (kappa, area under the curve of a receiver operating characteristic plot, and true skill statistic) did not differ between model predictions of roadside and off-road distributions of species. Furthermore, performance measures did not differ among edge, generalist, and interior species, despite a difference in vegetation structure along roadsides and off road and that 2 of the 15 species were more likely to occur along roadsides. If the range of environmental gradients is surveyed in roadside-sampling efforts, our results suggest that surveys along unpaved roads can be a valuable, unbiased source of information for species distribution models.     

Effects of tour boats on dolphin activity examined with sensitivity analysis of Markov chains

In Patagonia, Argentina, watching dolphins, especially dusky dolphins (Lagenorhynchus obscurus), is a new tourist activity. Feeding time decreases and time to return to feeding after feeding is abandoned and time it takes a group of dolphins to feed increase in the presence of boats. Such effects on feeding behavior may exert energetic costs on dolphins and thus reduce an individual's survival and reproductive capacity or maybe associated with shifts in distribution. We sought to predict which behavioral changes modify the activity pattern of dolphins the most. We modeled behavioral sequences of dusky dolphins with Markov chains. We calculated transition probabilities from one activity to another and arranged them in a stochastic matrix model. The proportion of time dolphins dedicated to a given activity (activity budget) and the time it took a dolphin to resume that activity after it had been abandoned (recurrence time) were calculated. We used a sensitivity analysis of Markov chains to calculate the sensitivity of the time budget and the activity-resumption time to changes in behavioral transition probabilities. Feeding-time budget was most sensitive to changes in the probability of dolphins switching from traveling to feeding behavior and of maintaining feeding behavior. Thus, an increase in these probabilities would be associated with the largest reduction in the time dedicated to feeding. A reduction in the probability of changing from traveling to feeding would also be associated with the largest increases in the time it takes dolphins to resume feeding. To approach dolphins when they are traveling would not affect behavior less because presence of the boat may keep dolphins from returning to feeding. Our results may help operators of dolphin-watching vessels minimize negative effects on dolphins.     

安全生产违章行为的人口因素影响模型研究——基于省级面板数据的协整方法

为了探讨人口因素对安全生产违章行为的影响,基于省级面板数据,构建安全生产违章行为数量与作业人员人口因素之间的固定效应变系数模型。实证研究,从业者的受教育程度、第二产业在岗职工平均工资以及人员数量规模等因素,影响违章行为方式及程度。结果表明:受教育程度的提高将显著抑制违章行为的发生;提高作业人员工资将增加违章行为的成本进而遏制违章行为的产生,但这一效果会受到作业人员所持有的风险态度的影响;作业人员规模的增加将提高工伤事故率。建议从提供受培训教育机会、提高违章成本、降低第二产业比重、减少高危行业作业人员数量等方面采取措施遏制违章行为。