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.     

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.     

吉林电网的暴雨灾害风险等级区划与评估研究

开展暴雨灾害对电网安全的风险等级区划与评估,可以指导电网的规划设计、建设、运行,最大限度保证电网安全.从风险评估四要素出发,充分考虑各要素的空间差异和权重差异,构建了等级划分标准,开展了风险区划和分区评价.结果表明:暴雨洪涝对吉林电网危害最高的地区是长春部分地区、吉林市辖区和通化的集安地区;其次是长春大部、四平大部、吉林部分地区和延边州的珲春部分地区;风险最低的地区主要在白城部分地区、白山部分地区及延边大部.从风险区划各指标的分析来看,通化地区南部的高风险性是由致灾因子的高危险性起主要作用,而吉林省中部地区的高、中风险性是由其孕灾环境的高敏感性及承灾体的高易损性引起的.     

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.     

电网调度系统安全运行评价指标体系研究

随着电力工业的迅速发展,电网调度自动化程度不断提高,电网调度面临新的形势:全国电网互联格局形成,电网运营的安全环境严峻。在对电网调度系统进行深入研究的基础上,通过问卷调查和专家咨询等方法获得了电网调度系统安全评价指标,采用层次分析法与模糊综合评价相结合的综合评价方法,最终建立了电网调度系统安全运行的指标体系,为电网调度系统的安全评价提供一定的参考。     

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。     

不同地铁车站吊顶形式对火灾烟气扩散的影响

针对实吊顶以及镂空率格栅吊顶装修形式的典型地铁车站站厅,采用大涡模拟的方法计算出不同镂空率吊顶在不同火源功率下的烟气层高度,分析评估镂空吊顶对烟气层沉降和温度分布。研究结果表明,火灾发生360 s内,格栅吊顶的蓄烟作用有助于将烟气层维持在安全高度,且随着镂空率增加维持烟气层在安全高度的效果越明显。但是镂空吊顶上方由于烟气温度较高,容易对吊顶内的各类设备产生危害。