Allelopathic inhibition on red tide microalgae Skeletonema costatum by five macroalgal extracts

This study aims to identify effective antialgal allelochemicals from marine macroalgae that inhibit the growth of red tide microalgae. Practically, new algicidal agents were developed to control red tide. The growth inhibitory effects of 5 marine macroalgae Porphyra tenera, Laminaria japonica, Ulva pertusa, Enteromorpha clathrata, and Undaria pinnatifida on Skeletonema costatum were evaluated by adding crude seawater extracts of macroalgal dry tissue into the culture medium containing S. costatum. The half-effective concentrations at 120 h (EC_{50, 120 h}) of the seawater extracts were 0.6, 0.9, 1.0, 1.0, and 4.7 g/L for the five macroalgae above, respectively. E. clathrata, L. japonica and U. pertusa showed strong allelopathic effect on the growth of S. costatum. There have been no previous reports with regard to the allelopathic effects of the former two macroalgae so far. The possible allelochemicals of 21 compounds of the E. clathrata were detected using Gas chromatography-mass spectrometry (GC-MS) analysis. Unsaturated fatty acids, acrylic acid (C₃H₄O₂), and linolenic acid (C₁₈H₃₀O₂) were the most likely allelochemicals in E. clathrata.     

Will progress in science and technology avert or accelerate global collapse? A critical analysis and policy recommendations

Industrial society will move towards collapse if its total environmental impact (I), expressed either in terms of energy and materials use or in terms of pollution, increases with time, i.e., dI/dt > 0. The traditional interpretation of the I = PAT equation reflects the optimistic belief that technological innovation, particularly improvements in eco-efficiency, will significantly reduce the technology (T) factor, and thereby result in a corresponding decline in impact (I). Unfortunately, this interpretation of the I = PAT equation ignores the effects of technological change on the other two factors: population (P) and per capita affluence (A). A more heuristic formulation of this equation is I = P(T)·A(T)·T in which the dependence of P and A on T is apparent. From historical evidence, it is clear that technological revolutions (tool-making, agricultural, and industrial) have been the primary driving forces behind successive population explosions, and that modern communication and transportation technologies have been employed to transform a large proportion of the world’s inhabitants into consumers of material- and energy-intensive products and services. In addition, factor analysis from neoclassical growth theory and the rebound effect provide evidence that science and technology have played a key role in contributing to rising living standards. While technological change has thus contributed to significant increases in both P and A, it has at the same time brought about considerable eco-efficiency improvements. Unfortunately, reductions in the T-factor have generally not been sufficiently rapid to compensate for the simultaneous increases in both P and A. As a result, total impact, in terms of energy production, mineral extraction, land-use and CO₂ emissions, has in most cases increased with time, indicating that industrial society is nevertheless moving towards collapse. The belief that continued and even accelerated scientific research and technological innovation will automatically result in sustainability and avert collapse is at best mistaken. Innovations in science and technology will be necessary but alone will be insufficient for sustainability. Consequently, what is most needed are specific policies designed to decrease total impact, such as (a) halting population growth via effective population stabilization plans and better access to birth control methods, (b) reducing total matter-energy throughput and pollution by removing perverse subsidies, imposing regulations that limit waste discharges and the depletion of non-renewable resources, and implementing ecological tax reform, and (c) moving towards a steady-state economy in which per-capita affluence is stabilized at lower levels by replacing wasteful conspicuous material consumption with social alternatives known to enhance subjective well-being. While science and technology must play an important role in the implementation of these policies, none will be enacted without a fundamental change in society’s dominant values of growth and exploitation. Thus, value change is the most important prerequisite for avoiding global collapse.

The Economic Effect of Mineral Resources Exploitation in Bijie Prefecture in Guizhou

Abstract

The exploitation of mineral resources plays an important role in promoting national economic development. Mining is an essential component of China’s industrial economy. Using grey correlation method to analyze the correlative effect of mineral resources exploitation to relevant industries, using national income method to calculate the pulling effect of mineral resources exploitation to economic growth and using graphs as well as tables to analyze the income distribution effect, the article obtains active economic effect of mineral resources development in Bijie, Guizhou. Moreover, from the view of resources-cored effect, the article analyzes negative effects such as single industrial structure brought by mineral resource development. Through analysis, we find that mineral resources exploitation to some extent brings active effects including gross domestic product growth, local financial revenue growth and relevant industries development; however, its negative effects should not be ignored. The negative effect can be lightened by diversifying industrial structure and prolonging industrial chain.     

冬奥会期间京津冀及周边区域空气质量时空特征、气象影响和减排效果评估

对比分析2015～2022年冬奥会期间(1月31日至2月20日)京津冀及周边区域44城市空气质量时空演变特征,量化同期气象、协同减排和跨区域传输对PM_2.5浓度及组分变化贡献,为不利气象条件下区域空气质量联防联控提供科学参考.结果表明,2022年44城市PM_2.5浓度为近8年农历同期最低(46μg·m^-3),优良天占比最高(83.3%),不存在重污染天.PM_2.5污染南重北轻,高值区主要集中在太行山沿线及燕山传输通道城市.2016年在春节中期未管控烟花爆竹燃放等源排放强度下,优良天占比93.5%,大气强扩散能力对空气质量改善至关重要.2022年静稳天气指数(SWI)同比增加2.1,大气扩散能力转差,44城市ρ(PM_2.5)均值和峰值同比下降14μg·m^-3和76μg·m^-3,北京减排对PM_2.5浓度降幅较未采取前增大96%,晋鲁豫地区在气象造成PM_2.5浓度上升的不利背景下,峰值下降87μg...     

Environmental and resource sustainability of Chinese cities: A review of issues,policies, practices and effects

This paper synthesizes the English literature on current issues, policies and practices, and their effects on environmental and resource sustainability in China's ongoing urbanization. Aspects of urban sustainability reviewed include air, water, solid waste, energy efficiency, transportation and land use. It shows that Chinese cities have been and probably will continue to be struggling with issues such as air pollution, scarcity of clean water, solid waste and greenhouse gas emissions. But there are many opportunities for improvement. It suggests shortages of existing policies and major gaps in knowledge and practice, which can be helpful to policy makers, planners and researchers in China and other developing countries.     

抗生素在环境中的迁移转化及生物效应研究进展

抗生素被长期大量地使用于人和动物的疾病治疗,同时作为饲料添加剂长期使用于畜牧业及水产养殖业。然而,大部分抗生素不能完全被机体吸收,大量的抗生素以原形或代谢物形式经由病人和禽畜粪尿排入环境,经不同途径进入土壤和水体,从而造成环境污染。多项研究显示在城镇废水和地表水中检测到了抗生素的存在,但关于抗生素在环境中的迁移转化及生物效应等研究资料很少。环境中的抗生素会对微生物、水生生物、土壤生物和植物等产生危害,并产生大量耐药菌,影响禽畜等的正常生长,进而对人类健康及整个生态系统构成威胁。为评估抗生素在环境中潜在的危害,本文就抗生素在环境中的迁移转化以及生物效应等多方面进行综述,并提出了今后研究的方向。     

提升高校环境教育效果的对策

本文论证了高校开展环境教育的必要性,总结了高校环境教育的现状,在分析导致高校环境教育效果差强人意的原因后,为提升高校环境教育效果,提出包括立法在内的一系列对策.     

陕西关中地区旅游流"井喷效应"的时空演变规律

旅游流"井喷现象"是特殊时段旅游流时空分布的特殊现象之一,其时空分布规律研究有助于旅游目的地的科学管理参照.选取关中地区旅游资源丰富的西安、宝鸡、华山三地作为案例,建立"黄金周"客流周内波动指数R,周内分布偏度指数G,并使用相关分析和Pearson相关系数,分析陕西关中地区特殊时段内旅游流"井喷效应"的时空演变规律.结果显示,在假日制度时间约束下,旅游流呈现"井喷现象"显著,一级旅游目的地城市的旅游资源属性、周边地区旅游资源配置和区位交通状况共同影响着游客的空间选择行为,从而影响区域旅游流的时间和空间分布.     

Forecasting population trend from the scaling pattern of occupancy

Forecasting the temporal trend of a focal species, its range expansion or retraction, provides crucial information regarding population viability. To this end, we require the accumulation of temporal records which is evidently time consuming. Progress in spatial data capturing has enabled rapid and accurate assessment of species distribution across large scales. Therefore, it would be appealing to infer the temporal trends of populations from the spatial structure of their distributions. Based on a combination of models from the fields of range dynamics, occupancy scaling and spatial autocorrelation, here I present a model for forecasting the population trend solely from its spatial distribution. Numerical tests using cellular automata confirm a positive correlation, as inferred from the model, between the temporal change in species range sizes and the exponent of the power-law scaling pattern of occupancy. The model is thus recommended for rapid estimation of species range dynamics from a single snapshot of its current distribution. Further applications in biodiversity conservation could provide a swift risk assessment, especially, for endangered and invasive species.