Short-term effects of gaseous pollutants on cause-specific mortality in Wuhan, China

In Asia, limited studies have been published on the association between daily mortality and gaseous pollutants of nitrogen dioxide (NO2), ozone (O3), and sulfur dioxide (SO2). Our previous studies in Wuhan, China, demonstrated long-term air pollution effects. However, no study has been conducted to determine mortality effects of air pollution in this region. This study was to determine the acute mortality effects of the gaseous pollutants in Wuhan, a city with 7.5 million permanent residents during the period from 2000 to 2004. There are approximately 4.5 million residents in Wuhan who live in the city's core area of 201 km2, where air pollution levels are highest, and pollution ranges are wider than the majority of the cities in the published literature. We used the generalized additive model to analyze pollution, mortality, and covariate data. We found consistent NO2 effects on mortality with the strongest effects on the same day. Every 10-microg/m3 increase in NO2 daily concentration on the same day was associated with an increase in nonaccidental (1.43%; 95% confidence interval [CI]: 0.87-1.99%), cardiovascular (1.65%; 95% CI: 0.87-2.45%), stroke (1.49%; 95% CI: 0.56-2.43%), cardiac (1.77%; 95% CI: 0.44-3.12%), respiratory (2.23%; 95% CI: 0.52-3.96%), and cardiopulmonary mortality (1.60%; 95% CI: 0.85-2.35%). These effects were stronger among the elderly than among the young. Formal examination of exposure-response curves suggests no-threshold linear relationships between daily mortality and NO2, where the NO2 concentrations ranged from 19.2 to 127.4 microg/m3. SO2 and O3 were not associated with daily mortality. The exposure-response relationships demonstrated heterogeneity, with some curves showing nonlinear relationships for SO2 and O3. We conclude that there is consistent evidence of acute effects of NO2 on mortality and suggest that a no-threshold linear relationship exists between NO2 and mortality.     

Application of artificial neural network approach and remotely sensed imagery for regional eco-environmental quality evaluation

Eco-environment quality evaluation is an important research theme in environment management. In the present study, Fuzhou city in China was selected as a study area and a limited number of 222 sampling field sites were first investigated in situ with the help of a GPS device. Every sampling site was assessed by ecological experts and given an Eco-environment Background Value (EBV) based on a scoring and ranking system. The higher the EBV, the better the ecological environmental quality. Then, three types of eco-environmental attributes that are physically-based and easily-quantifiable at a grid level were extracted: (1) remote sensing derived attributes (vegetation index, wetness index, soil brightness index, surface land temperature index), (2) meteorological attributes (annual temperature and annual precipitation), and (3) terrain attribute (elevation). A Back Propagation (BP) Artificial Neural Network (ANN) model was proposed for the EBV validation and prediction. A three-layer BP ANN model was designed to automatically learn the internal relationship using a training set of known EBV and eco-environmental attributes, followed by the application of the model for predicting EBV values across the whole study area. It was found that the performance of the BP ANN model was satisfactory and capable of an overall prediction accuracy of 82.4%, with a Kappa coefficient of 0.801 in the validation. The evaluation results showed that the eco-environmental quality of Fuzhou city is considered as satisfactory. Through analyzing the spatial correlation between the eco-environmental quality and land uses, it was found that the best eco-environmental areas were related to forest lands, whereas the urban area had the relatively worst eco-environmental quality. Human activities are still considered as a major impact on the eco-environmental quality in this area.     

RETRACTED ARTICLE: Environmental Impact Assessment of Industrial Structure Change in a Rural Region of China

As the embodiment of human activities, the change of regional industrial structure is an essential driving factor of global environmental change. Consequently, the research on the change of regional industrial structure and associated effects on the environment is one of the key issues of researches on sustainable development, human–environment relationship, and regional response to global environment change. However, compared to the flourish of researches on environmental impact assessment of industrial departments, few studies have been conducted to assess the environmental impact of regional industrial structure. In this study, based on a synthetic analysis of environmental disturbances of different industrial departments, the environmental impact coefficient of industrial department associated with the index of environmental impact of industrial structure was constructed, so as to make a quantitative assessment of environmental impact of the change of regional industrial structure. And the results of the case study in Lijiang City, a rural region of China, have showed that there are two obvious changes of industrial structure in the study area from 1992 to 2003, associated with a continuous decreasing of the index of environmental impact of industrial structure, which indicated a positive environmental effects of the change of regional industrial structure.     

Training Captive-Bred or Translocated Animals to Avoid Predators

Abstract: Animal reintroductions and translocations are potentially important interventions to save species from extinction, but most are unsuccessful. Mortality due to predation is a principal cause of failure. Animals that have been isolated from predators, either throughout their lifetime or over evolutionary time, may no longer express appropriate antipredator behavior. For this reason, conservation biologists are beginning to include antipredator training in pre-release preparation procedures. We describe the evolutionary and ontogenetic circumstances under which antipredator behavior may degenerate or be lost, and we use principles from learning theory to predict which elements can be enhanced or recovered by training. The empirical literature demonstrates that training can improve antipredator skills, but the effectiveness of such interventions is influenced by a number of constraints. We predict that it will be easier to teach animals to cope with predators if they have experienced ontogenetic isolation than if they have undergone evolutionary isolation. Similarly, animals should learn more easily if they have been evolutionarily isolated from some rather than all predators. Training to a novel predator may be more successful if a species has effective responses to similar predators. In contrast, it may be difficult to teach proper avoidance behavior, or to introduce specialized predator-specific responses, if appropriate motor patterns are not already present. We conclude that pre-release training has the potential to enhance the expression of preexisting antipredator behavior. Potential training techniques involve classical conditioning procedures in which animals learn that model predators are predictors of aversive events. However, wildlife managers should be aware that problems, such as the emergence of inappropriate responses, may arise during such training.     

An Evaluation of Restoration Efforts in Fishless Lakes Stocked with Exotic Trout

Abstract: Detrimental effects of introduced fishes on native amphibian populations have prompted removal of introduced cutthroat ( Oncorhynchus clarki ), rainbow ( Oncorhynchus mykiss ), and brook trout (  Salvelinus fontinalis ) from naturally fishless lakes at Mt. Rainier National Park, Washington ( U.S.A.). Using paleolimnological indicators (diatoms, invertebrates, and sediment characteristics) in eight 480-year-old sediment cores from eight lakes, we (1) derived estimates of baseline environmental conditions and natural variation, (2) assessed the effects of stocking naturally fishless lakes, and (3) determined whether lakes returned to predisturbance conditions after fish removal (restoration). Diatom floras were relatively stable between 315 and 90 years before present in all lakes; we used this time period to define lake-specific "baseline" conditions. Dissimilarity analyses of diatoms revealed sustained, dramatic changes in diatom floras that occurred approximately 80 years ago (when fish were introduced) in four of five stocked lakes, whereas the diatom floras in two unstocked lakes had not changed significantly in the last 315 years. Diatoms were not preserved in an eighth lake. State changes also occurred in two lakes over 200 years before European settlement of the Pacific Northwest. Preserved invertebrate densities fluctuated dramatically over time in all cores, providing a poor reference for assessing the effects of fishes. Nevertheless, fish-invertebrate interactions have been demonstrated in other paleolimnological studies and may be useful for lower-elevation or more productive lakes. Because diatom communities have not returned to predisturbance assemblages in restored lakes, even 20–30 years after fish removal, we conclude that Mt. Rainier lakes were not successfully restored by the removal of fishes.     

Bushmeat Markets on Bioko Island as a Measure of Hunting Pressure

Abstract: Counts of the number of animal carcasses arriving at Malabo market, Bioko Island, Equatorial Guinea, were made during two, 8-month study periods in 1991 and 1996. Comparisons of the availability and abundance of individual species between years showed that more species and more carcasses appeared in 1996 than in 1991. In biomass terms, the increase was significantly less, only 12.5%, when compared with almost 60% more carcasses entering the market in 1996. A larger number of carcasses of the smaller-bodied species (i.e., rodents and the blue duiker [ Cephalophus monticola ] ) were recorded in 1996 than in 1991. Although an additional four species of birds and one squirrel were recorded in 1996, these were less important in terms of their contribution to biomass or carcass numbers. Concurrently, there was a dramatic reduction in the larger-bodied species, Ogilby's duiker ( C. ogilbyi ) and seven diurnal primates. We examined these changes, especially the drop in the number of larger animals. We considered the possible following explanations: (1) the number of hunters dropped either because of enforced legislation or scarcity of larger prey; (2) a shift in the use of hunting techniques occurred (   from shotguns to snares); or (3) consumer demand for primate and duiker meat dropped, which increased demand for smaller game. Our results suggest that the situation in Bioko may be alarmingly close to a catastrophe in which primate populations of international conservation significance are being hunted to dangerously low numbers. Although there is still a need for surveys of actual densities of prey populations throughout the island, working with the human population on Bioko to find alternatives to bushmeat is an urgent priority.     

Will Observation Error and Biases Ruin the Use of Simple Extinction Models?

Abstract: Estimating the risk of extinction for populations of endangered species is an important component of conservation biology. These estimates must be made from data that contain both environmental noise in the year-to-year transitions in population size (so-called "process error"), random errors in sampling, and possible biases in sampling ( both forms of observation errors). To determine how much faith to place in estimated extinction rates, it is important to know how sensitive they are to observation error. We used three simple, commonly employed models of population dynamics to generate simulated population time series. We then combined random observation error or systematic biases with those data, fit models to the time series data, and observed how close the extinction dynamics of the fitted models compared with the dynamics of the underlying models. We found that systematic biases in sampling rarely affected estimates of extinction risk. We also found that even moderate levels of random observation error do not significantly affect extinction estimates except over a small range of process errors, corresponding to the region where extinction risk is most uncertain. With more substantial sampling error, estimates of extinction risk degraded rapidly. Field census techniques for a variety of taxa often involve observation errors within ±32% of actual population sizes. For typical time series used in conservation, therefore, we often may not need to be overly concerned about observation errors as an extra source of imperfection in our estimated extinction rates.     

Demographic Forecasting in Koala Conservation

Abstract: The koala currently needs conservation intervention. There is clear evidence of decline in many populations, but the existence of other stable or expanding populations offers the possibility of a variety of creative solutions to their conservation problems. The 1998 National Koala Conservation Strategy emphasizes the need to obtain demographic information and to use this information to assess management options for koalas. We need accurate diagnoses of the status of koala populations and forecasts of their demographic future with and without particular management actions. In a qualitative fashion, this process has been undertaken many times on a local and national scale. Quantitative demographic forecasting tools are increasingly available, and koala management could benefit from their application both at the scale of individual populations and more broadly. There is already a considerable body of suitable data on the dispersal, effects of normal and catastrophic environmental variation on reproduction and survival, and on the effects of habitat change. Demographic forecasting, however, is hampered because the full suite of information is rarely available from a single population. In two Queensland populations, retrospective population viability analyses provided forecasts that were in agreement with observed population trends. Work is needed to determine whether data from one population can be applied to other populations. Models can then be developed to make projections at a multipopulation level on the basis of local population dynamics and dispersal. Certain koala populations, because of their long history of study, offer the opportunity to test demographic models retrospectively. These tests will not only aid in fine-tuning the models for koala biology and data but will also assist with the more general process of validating the models.