Defining the Impact of Non‐Native Species

Non‐native species cause changes in the ecosystems to which they are introduced. These changes, or some of them, are usually termed impacts; they can be manifold and potentially damaging to ecosystems and biodiversity. However, the impacts of most non‐native species are poorly understood, and a synthesis of available information is being hindered because authors often do not clearly define impact. We argue that explicitly defining the impact of non‐native species will promote progress toward a better understanding of the implications of changes to biodiversity and ecosystems caused by non‐native species; help disentangle which aspects of scientific debates about non‐native species are due to disparate definitions and which represent true scientific discord; and improve communication between scientists from different research disciplines and between scientists, managers, and policy makers. For these reasons and based on examples from the literature, we devised seven key questions that fall into 4 categories: directionality, classification and measurement, ecological or socio‐economic changes, and scale. These questions should help in formulating clear and practical definitions of impact to suit specific scientific, stakeholder, or legislative contexts. Definiendo el Impacto de las Especies No‐Nativas     

Toward a new understanding of the links between poverty and illegal wildlife hunting

Conservation organizations have increasingly raised concerns about escalating rates of illegal hunting and trade in wildlife. Previous studies have concluded that people hunt illegally because they are financially poor or lack alternative livelihood strategies. However, there has been little attempt to develop a richer understanding of the motivations behind contemporary illegal wildlife hunting. As a first step, we reviewed the academic and policy literatures on poaching and illegal wildlife use and considered the meanings of poverty and the relative importance of structure and individual agency. We placed motivations for illegal wildlife hunting within the context of the complex history of how wildlife laws were initially designed and enforced to indicate how hunting practices by specific communities were criminalized. We also considered the nature of poverty and the reasons for economic deprivation in particular communities to indicate how particular understandings of poverty as material deprivation ultimately shape approaches to illegal wildlife hunting. We found there is a need for a much better understanding of what poverty is and what motivates people to hunt illegally.     

The Value of Using Feasibility Models in Systematic Conservation Planning to Predict Landholder Management Uptake

Understanding the social dimensions of conservation opportunity is crucial for conservation planning in multiple‐use landscapes. However, factors that influence the feasibility of implementing conservation actions, such as the history of landscape management, and landholders’ willingness to engage are often difficult or time consuming to quantify and rarely incorporated into planning. We examined how conservation agencies could reduce costs of acquiring such data by developing predictive models of management feasibility parameterized with social and biophysical factors likely to influence landholders’ decisions to engage in management. To test the utility of our best‐supported model, we developed 4 alternative investment scenarios based on different input data for conservation planning: social data only; biological data only; potential conservation opportunity derived from modeled feasibility that incurs no social data collection costs; and existing conservation opportunity derived from feasibility data that incurred collection costs. Using spatially explicit information on biodiversity values, feasibility, and management costs, we prioritized locations in southwest Australia to control an invasive predator that is detrimental to both agriculture and natural ecosystems: the red fox (Vulpes vulpes). When social data collection costs were moderate to high, the most cost‐effective investment scenario resulted from a predictive model of feasibility. Combining empirical feasibility data with biological data was more cost‐effective for prioritizing management when social data collection costs were low (<4% of the total budget). Calls for more data to inform conservation planning should take into account the costs and benefits of collecting and using social data to ensure that limited funding for conservation is spent in the most cost‐efficient and effective manner.     

城市绿色建筑与可持续发展探析

结合我国国情,对绿色建筑的基本概念和要达到的目标进行了分析。综合可持续发展评价体系以及我国目前在绿色建筑方面的发展进程,提出全面推进绿色建筑,完善建筑业可持续发展体系的措施建议。     

辽宁省经济发展与环境关系的实证研究

维持经济的持续稳定增长是我国的重要政策目标,然而面对日趋严峻的资源、环境制约,大力推进生态文明建设已刻不容缓。相应地,在理论方面,研究经济增长与环境污染的双向作用机制也非常必要。利用VAR模型,研究了辽宁省经济发展与环境之间的关系,发现两者之间的关系并不是EKC理论中所说的倒u型曲线,而是呈现w型、N型等更加复杂的曲线形状。实验结果也表明辽宁省环境与经济存在双向作用机制,其中,废气与废水对辽宁省经济增长影响最大。     

从经济学角度对比中国与美国的能源消费

分析了中关两国能源消费总量和能源结构的差异,探讨了中关两国能源消费差异的经济学内涵,认为经济指标GDP并不能完全反映人们生活水平的提高,而其带来的环境问题却很可能影响后续的经济发展。因此,在发展经济的同时,应该充分考虑能源需求给环境带来的压力。适当调整能源结构、提高能源效率和发展替代能源是未来能源消费战略的重中之重,也是经济、环境和社会协调发展的重要保障。     

生物过滤塔净化甲醛废气的动力学研究

选用榛子壳作为反应器的填料,利用沈阳北部污水处理厂的活性污泥对填料进行挂膜,由低到高通入甲醛气体进行驯化。在系统稳定后进行了生物过滤塔净化甲醛气体的实验研究,并建立了生物过滤塔降解甲醛气体的动力学模型。结果表明,入口气体浓度在低于25mg/m3时,甲醛废气的净化效率可保持在97％以上,超过此浓度值时,效率明显下降。随着进口气体流量的增加,净化率逐渐下降,由入口流量为0．2m3／h时的97．25％下降到入口流量为0．8m弧时的57．2％。根据现有动力学模型及本实验得出数据所建立的生物过滤塔净化甲醛气体的动力学模型,可以较好地模拟系统处理甲醛废气的实验结果,验证了模型的正确性。     

中水回用与效益分析

当前我国水资源供需矛盾日益加剧,实现中水利用是节约水资源的一条有效途径.通过分析中水水源、MBR处理技术及中水用途,结合一个高校实例,进行经济效益分析,并对建设中水回用系统的可行性进行论证.经计算可得效益费用比达到2.38,经济效益是非常明显的,具有实际的参考价值.中水回用不仅节约了水资源而且也产生了明显的经济效益,是城市发展的趋势.     

发展低碳经济建设生态环保城市

生态环保城市的建设,必须走低碳经济之路。要大力发展生态环保产业,调整高碳产业结构,提高城市生态环保的意识。     

Modelling Phosphorus Retention in Lakes and Reservoirs

Steady-state models for the prediction of P retention coefficient (R) in lakes were evaluated using data from 93 natural lakes and 119 reservoirs situated in the temperate zone. Most of the already existing models predicted R relatively successfully in lakes while it was seriously under-estimated in reservoirs. A statistical analysis indicated the main causes of differences in R between lakes and reservoirs: (a) distinct relationships between P sedimentation coefficient, depth, and water residence time; (b) existence of significant inflow–outflow P concentration gradients in reservoirs. Two new models of different complexity were developed for estimating R in reservoirs: , where τ is water residence time (year), was derived from the Vollenweider/Larsen and Mercier model by adding a calibrated parameter accounting for spatial P non-homogeneity in the water body, and is applicable for reservoirs but not lakes, and , where [P_in] is volume-weighted P concentration in all inputs to the water body (μg l⁻¹), was obtained by re-calibrating the OECD general equation, and is generally applicable for both lakes and reservoirs. These optimised models yield unbiased estimates over a large range of reservoir types.