Accounting for large-scale factors in the study of understory vegetation using a conditional logistic model

Local-scale and large-scale factors can affect the presence of a species of understory vegetation in the forest. Local-scale factors may be the influence of surrounding trees, while climate and latitude are typically considered large-scale factors. A model for the presence of a species needs to take into account both scales. A conditional logistic model is proposed for those studies where only the local-scale factors are of interest and that avoids estimating the large-scale parameters. Conditioning is carried out by the number of quadrats in the plot where the vegetation is found. As the latter is a sufficient statistic for the large-scale factors, a model free from these parameters is obtained. Data gathered in the permanent sample plots of the 1985–1986 National Forest Inventory of Finland is used for illustration, where the local-scale factor of interest is the influence of the trees, quantified by an index based on the size and location of the trees. The model fitted to Vaccinium vitis-idaea showed a significant and positive influence of Scots pine on the presence of this species, while for Calamagrostis arundinacea, a decrease in the odds ratio was observed due to the influence of Norway spruce.     

Objective and quantitative evaluation of environmental quality of the land for agriculture purpose

An objective and quantitative evaluation method on land environmental quality for agricultural purpose in a county range is studied in this paper. The method takes into account the quantity of heat, precipitation, meteorological disaster and soil fertility, which have close relationship to the potential productivity of land and can be expressed conveniently and accurately by taking Kai County as an example. Besides comprehensive grading assessment, assessment with Hilbert Space distance coefficiency and comprehensive judgement by fuzzy sets theory, the assessment factors are expanded to 18 parameters, and fuzzy dominance matrix and fuzzy clustering methods are adopted for regional comprehensive identification of agriculture-use land. Among these methods, each benefits from association with the other. In this paper, an all-round and objective new way for understanding of land environmental quality is put forward.     

对氨基苯甲醚废水处理

对氨基苯甲醚生产中排放的废水经物化前处理后,利用二氧化氯为氧化剂,在自制催化剂存在的条件下将废水中的有机物氧化分解,使CODCR去除率≥70％,色度去除率≥85％,硝基苯去除率≥85％,挥发酚去除率≥80％,氧化处理后再进行生化处理,该废水可以达标排放。     

Detection and mapping of water pollution variation in the Nile Delta using multivariate clustering and GIS techniques

The limited water resources of Egypt lead to widespread water-stress. Consequently, the use of marginal water sources, such as agricultural drainage waters, provides one of the national feasible solutions to the problem. However, the marginal quality of the drainage waters may restrict their use.The objective of this research is to develop a tool for planning and managing the reuse of agricultural drainage water for irrigation in the Nile Delta. This is achieved by classifying the pollution levels of drainage water into several categories using a statistical clustering approach that may ensure simple but accurate information about the pollution levels and water characteristics at any point within the drainage system.The derived clusters are then visualized by using a Geographical Information System (GIS) to draw thematic maps based on the entire Nile Delta, thus making GIS as a decision support system. The obtained maps may assist the decision makers in managing and controlling pollution in the Nile Delta regions. The clustering process also provides an effective overview of those spots in the Nile Delta where intensified monitoring activities are required. Consequently, the obtained results make a major contribution to the assessment and redesign of the Egyptian national water quality monitoring network.     

An analysis of China’s investment in the hydropower sector in the Greater Mekong Sub-Region

The Mekong River’s natural resources offer large benefits to its populations, but it also attracts the interest of foreign investors. Recently, Chinese firms, banks and government bodies have increasingly invested in large hydropower projects in the Greater Mekong Sub-Region. Due to China’s rapid economic growth, its rapid industrialisation and its limited domestic natural resources, the Chinese government has issued the ‘Going Out Strategy’ which promotes investments in overseas natural resources like water and energy resources. In search for climate-friendly low-carbon energy, cheap electricity and access to a growing market, Chinese institutions turn to Southeast Asia where Chinese institutions are currently involved in more than 50 on-going large hydropower projects as contractors, investors, regulators and financiers. These Chinese institutions have influence on environmental and social practices as well as on diplomatic and trade relations in the host countries. Currently, there are major gaps in understanding who is engaged, why, how and with what impacts. This paper therefore aims to assess the motives, actors, beneficiaries and the direct and indirect impacts of China’s investment in large hydropower projects in the Greater Mekong Sub-Region. The authors use the ‘Rising Powers Framework’ to assess these issues, which is an adapted version of the Asian Drivers Framework.     

Evolving metacommunities: toward an evolutionary perspective on metacommunities

The metacommunity framework predicts that local coexistence depends on the outcome of local species interactions and regional migration. In analogous fashion, spatial structure among populations can shape species interactions through evolutionary mechanisms. Yet, most metacommunity theories assume that populations do not evolve. Here, we evaluate how evolution shapes local species coexistence and exclusion within the multiscale and multispecies context embodied by the metacommunity framework. In general, coexistence in joint ecological-evolutionary models requires low to intermediate dispersal rates that can promote maintenance of both regional species and genetic diversity. These conditions support a set of key mechanisms that modify patterns of species coexistence including local adaptation, gene storage effects, genetic rescue effects, spatial genetic subsidies, and metacommunity evolution. Multispecies extensions indicate that correlated selection can further alter the outcome of interspecific interactions depending on the magnitude and direction of correlations and shape of fitness trade-offs. We suggest that an evolving metacommunity perspective has the potential to generate novel predictions about community structure and function by incorporating the genetic and species diversity that characterize natural communities. In adopting such a perspective, we seek to facilitate understanding about the interactions between evolutionary and metacommunity dynamics.     

COVID-19 pandemic: environmental and social factors influencing the spread of SARS-CoV-2 in São Paulo,Brazil

Environmental Science and Pollution Research - The new coronavirus SARS-CoV-2 has infected more than 14 million people worldwide so far. Brazil is currently the second leading country in number of...     

人工神经网络在沿海区域环境复杂系统预测中的应用

针对复杂系统的非线性特征，分析了应用人工神经网络技术实现可持续发展复杂系统预测的可能性，并以上海市和崇明县为例建立沿海区域预测模型，取得了较好的预测结果，为可持续发展复杂系统的预测研究探索了一种新的可能方法。     

大亚湾开发区排污权交易实施方案研究

为保护大亚湾开发区的环境,充分运用社会主义市场经济手段配置环境资源,提高环保投资效益,在国内外排污权交易研究和实践的基础上,充分考虑环境污染物排放总量控制实施中的经济、技术、管理因素,提出了排污权交易实施的原则、程序等具体方案,明确了环境行政管理部门和企业法人在总量控制实施中的地位、具体行为和关系。研究结果已经在大亚湾开发区应用。     

The growth-predation risk trade-off under a growing gape-limited predation threat

Growth is a critical ecological trait because it can determine population demography, evolution, and community interactions. Predation risk frequently induces decreased foraging and slow growth in prey. However, such strategies may not always be favored when prey can outgrow a predator's hunting ability. At the same time, a growing gape-limited predator broadens its hunting ability through time by expanding its gape and thereby creates a moving size refuge for susceptible prey. Here, I explore the ramifications of growing gape-limited predators for adaptive prey growth. A discrete demographic model for optimal foraging/growth strategies was derived under the realistic scenario of gape-limited and gape-unconstrained predation threats. Analytic and numerical results demonstrate a novel fitness minimum just above the growth rate of the gape-limited predator. This local fitness minimum separates a slow growth strategy that forages infrequently and accumulates low but constant predation risk from a fast growth strategy that forages frequently and experiences a high early predation risk in return for lower future predation risk and enhanced fecundity. Slow strategies generally were advantageous in communities dominated by gape-unconstrained predators whereas fast strategies were advantageous in gape-limited predator communities. Results were sensitive to the assumed relationships between prey size and fecundity and between prey growth and predation risk. Predator growth increased the parameter space favoring fast prey strategies. The model makes the testable predictions that prey should not grow at the same rate as their gape-limited predator and generally should grow faster than the fastest growing gape-limited predator. By focusing on predator constraints on prey capture, these results integrate the ecological and evolutionary implications of prey growth in diverse predator communities and offer an explanation for empirical growth patterns previously viewed to be anomalies.