Progress and challenges in consolidating the management of Amazonian protected areas and indigenous territories

Effective management refers to the ability of a protected area or indigenous territory to meet its objectives, particularly as they relate to the protection of biodiversity and forest cover. Effective management is achieved through a process of consolidation, which among other things requires legally protecting sites, integrating sites into land‐use planning, developing and implementing management and resource‐use plans, and securing long‐term funding to pay for recurrent costs. Effectively managing all protected areas and indigenous territories in the Amazon may be needed to avoid a deforestation tipping point beyond which regional climatic feedbacks and global climate change interact to catalyze irreversible drying and savannization of large areas. At present, protected areas and indigenous territories cover 45.5% (3.55 million km²) of the Amazon, most of the 60–70% forest cover required to maintain hydrologic and climatic function. Three independent evaluations of a long‐term large‐scale philanthropic initiative in the Amazon yielded insights into the challenges and advances toward achieving effective management of protected areas and indigenous territories. Over the life of the initiative, management of sites has improved considerably, particularly with respect to management planning and capacity building, but few sites are effectively managed and many lack sufficient long‐term financing, adequate governance, support of nongovernmental organizations, and the means to withstand economic pressures. The time and money required to complete consolidation is still poorly understood, but it is clear that philanthropic funding is critical so long as essential funding needs are not met by governments and other sources, which could be on the order of decades. Despite challenges, it is encouraging that legal protection has expanded greatly and management of sites is improving steadily. Management of protected areas in other developing countries could be informed by improvements that have occurred in Amazonian countries.     

Understanding implications of consumer behavior for wildlife farming and sustainable wildlife trade

Unsustainable wildlife trade affects biodiversity and the livelihoods of communities dependent upon those resources. Wildlife farming has been proposed to promote sustainable trade, but characterizing markets and understanding consumer behavior remain neglected but essential steps in the design and evaluation of such operations. We used sea turtle trade in the Cayman Islands, where turtles have been farm raised for human consumption for almost 50 years, as a case study to explore consumer preferences toward wild‐sourced (illegal) and farmed (legal) products and potential conservation implications. Combining methods innovatively (including indirect questioning and choice experiments), we conducted a nationwide trade assessment through in‐person interviews from September to December 2014. Households were randomly selected using disproportionate stratified sampling, and responses were weighted based on district population size. We approached 597 individuals, of which 37 (6.2%) refused to participate. Although 30% of households had consumed turtle in the previous 12 months, the purchase and consumption of wild products was rare (e.g., 64–742 resident households consumed wild turtle meat [i.e., 0.3–3.5% of households] but represented a large threat to wild turtles in the area due to their reduced populations). Differences among groups of consumers were marked, as identified through choice experiments, and price and source of product played important roles in their decisions. Despite the long‐term practice of farming turtles, 13.5% of consumers showed a strong preference for wild products, which demonstrates the limitations of wildlife farming as a single tool for sustainable wildlife trade. By using a combination of indirect questioning, choice experiments, and sales data to investigate demand for wildlife products, we obtained insights about consumer behavior that can be used to develop conservation‐demand‐focused initiatives. Lack of data from long‐term social–ecological assessments hinders the evaluation of and learning from wildlife farming. This information is key to understanding under which conditions different interventions (e.g., bans, wildlife farming, social marketing) are likely to succeed.     

Emerging applications of green coconut: A promising lignocellulosic biomass

Waste accumulation is a grave concern and becoming a transboundary challenge for environment. During Covid-19 pandemic, diverse type of waste were collected due to different practices employed in order to fight back the transmission rate of the virus. Covid-19 was proved to be capricious catastrophe of this 20th century and even not completely eradicated from the world. The havoc created by this imperceptible quick witted, pleomorphic deadly virus can't be ignored. Though a number of vaccines have been developed by the scientists but there is a fear of getting this virus again in our life. Medical studies prove that immunity drinks will help to reduce its reoccurrences. Coconut water is widely used among all drinks available globally. Its massive consumption created an incalculable pile of green coconut shells around the different corners of the world. This practice generating enormous problem of space acquisition for the environment. Both the environment and public health will benefit from an evaluation of quantity of coconut waste that is being thrown and its potential to generate value added products. With this context, present article has been planned to study different aspects like, coconut waste generation, its biological properties and environmental hazards associated with its accumulation. Additionally, this review illustrates, green technologies for production of different value added products from coconut waste.     

基于复杂系统建模的水管理政策研究进展

基于Agent的建模方法（ABSS）通过自下而上的方式，考察系统中主体的不同状态和行为特征、主体与环境的作用、主体之间的作用，来表征系统的宏观特征，是进行复杂社会环境系统分析和政策研究的重要手段，在水资源、水环境管理系统中得到了有效的应用。本文在大量文献调研的基础上，讨论了ABSS建模方法的基本原理、主要特征、系统构成、分类方法和开发工具等特征，总结了其供水系统发展、水资源分配和流域水资源管理、农业土地和水资源利用、居民用水行为、农业污染控制及人类活动的水环境影响等方面的应用，分析了其在研究内容、研究方法、研究结果等方面的发展趋势，讨论了利用该方法研究我国水资源管理和水污染控制政策的必要性和重要性。     

Effects of Coastal Lighting on Foraging Behaviorof Beach Mice

Abstract:  Introduction of artificial light into wildlife habitat represents a rapidly expanding form of human encroachment, particularly in coastal systems. Light pollution alters the behavior of sea turtles during nesting; therefore, long-wavelength lights—low-pressure sodium vapor and bug lights—that minimize impacts on turtles are required for beach lighting in Florida (U.S.A.). We investigated the effects of these two kinds of lights on the foraging behavior of Santa Rosa beach mice (  Peromyscus polionotus leucocephalus ). We compared patch use and giving-up densities of mice for experimental food patches established along a gradient of artificial light in the field. Mice exploited fewer food patches near both types of artificial light than in areas with little light and harvested fewer seeds within patches near bug lights. Our results show that artificial light affects the behavior of terrestrial species in coastal areas and that light pollution deserves greater consideration in conservation planning.     

Analysis of the Trend and Seasonal Cycle of Carbon Monoxide Concentrations in an Urban Area (4 pp)

Background, Aim and Scope Air quality is an field of major concern in large cities. This problem has led administrations to introduce plans and regulations to reduce pollutant emissions. The analysis of variations in the concentration of pollutants is useful when evaluating the effectiveness of these plans. However, such an analysis cannot be undertaken using standard statistical techniques, due to the fact that concentrations of atmospheric pollutants often exhibit a lack of normality and are autocorrelated. On the other hand, if long-term trends of any pollutant’s emissions are to be detected, meteorological effects must be removed from the time series analysed, due to their strong masking effects. Materials and Methods The application of statistical methods to analyse temporal variations is illustrated using monthly carbon monoxide (CO) concentrations observed at an urban site. The sampling site is located at a street intersection in central Valencia (Spain) with a high traffic density. Valencia is the third largest city in Spain. It is a typical Mediterranean city in terms of its urban structure and climatology. The sampling site started operation in January 1994 and monitored CO ground level concentrations until February 2002. Its geographic coordinates are W0°22′52″ N39°28′05″ and its altitude is 11 m. Two nonparametric trend tests are applied. One of these is robust against serial correlation with regards to the false rejection rate, when observations have a strong persistence or when the sample size per month is small. A nonparametric analysis of the homogeneity of trends between seasons is also discussed. A multiple linear regression model is used with the transformed data, including the effect of meteorological variables. The method of generalized least squares is applied to estimate the model parameters to take into account the serial dependence of the residuals of this model. This study also assesses temporal changes using the Kolmogorov-Zurbenko (KZ) filter. The KZ filter has been shown to be an effective way to remove the influence of meteorological conditions on O₃ and PM to examine underlying trends. Results The nonparametric tests indicate a decreasing, significant trend in the sampled site. The application of the linear model yields a significant decrease every twelve months of 15.8% for the average monthly CO concentration. The 95% confidence interval for the trend ranges from 13.9% to 17.7%. The seasonal cycle also provides significant results. There are no differences in trends throughout the months. The percentage of CO variance explained by the linear model is 90.3%. The KZ filter separates out long, short-term and seasonal variations in the CO series. The estimated, significant, long-term trend every year results in 10.3% with this method. The 95% confidence interval ranges from 8.8% to 11.9%. This approach explains 89.9% of the CO temporal variations. Discussion The differences between the linear model and KZ filter trend estimations are due to the fact that the KZ filter performs the analysis on the smoothed data rather than the original data. In the KZ filter trend estimation, the effect of meteorological conditions has been removed. The CO short-term componentis attributable to weather and short-term fluctuations in emissions. There is a significant seasonal cycle. This component is a result of changes in the traffic, the yearly meteorological cycle and the interactions between these two factors. There are peaks during the autumn and winter months, which have more traffic density in the sampled site. There is a minimum during the month of August, reflecting the very low level of vehicle emissions which is a direct consequence of the holiday period. Conclusions The significant, decreasing trend implies to a certain extent that the urban environment in the area is improving. This trend results from changes in overall emissions, pollutant transport, climate, policy and economics. It is also due to the effect of introducing reformulated gasoline. The additives enable vehicles to burn fuel with a higher air/fuel ratio, thereby lowering the emission of CO. The KZ filter has been the most effective method to separate the CO series components and to obtain an estimate of the long-term trend due to changes in emissions, removing the effect of meteorological conditions. Recommendations and Perspectives Air quality managers and policy-makers must understand the link between climate and pollutants to select optimal pollutant reduction strategies and avoid exceeding emission directives. This paper analyses eight years of ambient CO data at a site with a high traffic density, and provides results that are useful for decision-making. The assessment of long-term changes in air pollutants to evaluate reduction strategies has to be done while taking into account meteorological variability     

灰色协调度模型在产业用水系统分析中的应用

揭示产业用水系统的时空动态发展规律，探讨其内部的协调关系，是开展节水型社会建设规划，实现水资源可持续利用的关键。然而，目前对产业用水系统的协调性分析还缺乏较为有效的理论和方法。以往在利用协调度模型进行用水系统有序度研究时，通常采用两段叙述的线性分段函数表示，较不适用于描述产业用水系统内部要素的非线性结构。因此，针对产业用水系统的特性，利用灰关联原理建立有序度函数，以建立更适于用水系统分析的灰色协调度模型。利用该模型对上海市1997~2005年产业用水系统进行实证研究，结果显示：上海市产业用水系统基本有序，发展比较协调，其用水综合效益较大，但距离最优状态尚有潜力可挖；其中，农业用水子系统的发展较为欠缺，在未来用水规划中应予以重视。     

核算间接冷却水污染当量数的研讨

针对间接冷却水的特点和核算其污染当量数过程中存在的问题，阐述了间接冷却水的界定，水源水的采样监测技术，本底值的扣除以及超标排放的判别等环节的技术要求和注意事项，并就与之密切相关的几个问题展开了讨论,为核算间接冷却水当量数提供了一定的参考依据，建议增加水湿排放指标，以切实控制间接冷却水造成的主要污染－热污染。