Using culturomics and social media data to characterize wildlife consumption

Wildlife provides food, medicine, clothing, and other necessities for humans, but overexploitation can disrupt the sustainability of wildlife resources and severely threaten global biodiversity. Understanding the characteristics of consumer behavior is helpful for wildlife managers and policy makers, but the traditional survey methods are laborious and time-consuming. In contrast, culturomics may more efficiently identify the features of wildlife consumption. As a case study of the culturomics approach, we examined tiger bone wine consumption in China based on social media and Baidu search engine data. Tiger bone wine is one of the most purchased tiger products; its consumption is closely related to tiger poaching, which greatly threatens wild tiger survival. We searched a popular social media website for the term “tiger bone wine” and focused on posts that were originally created from 1 January 2012 to 31 December 2018. We filtered and classified posts related to the purchase, sale, or consumption of tiger bone wine and extracted information on providers, consumption motivations, year of production, and place of origin of the tiger bone wines based on the texts and photos of these posts. We found 756 posts related to tiger bone wine consumption, 113 of which mentioned providers of tiger bone wine, including friends (53%), elder relatives (37%), peer relatives (7%), and others (3%). Out of the 756 posts, 266 indicated the motivations of tiger bone wine consumption. Tiger bone wines were consumed as a tonic (34%), medicine (23%), game product (30%), and a symbol of wealth (28%). Some posts indicated ≥2 consumption motivations. These findings were consistent with the search queries from Baidu index. Such information could help develop targeted strategies for tiger conservation. The culturomics approach illustrated by our study is a rapid and cost-efficient way to characterize wildlife consumption.     

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     

Exploring Chemical Variables in Ligustrum lucidum Ait. F. Tricolor (Rehd.) Rehd. in Relation to Air Pollutants and Environmental Conditions

Ligustrum lucidum Ait. f. tricolor (Rehd.) Rehd. in relation to atmospheric pollutants in Córdoba city, Argentina. The study area receives regional pollutants and was categorized taking into account traffic level, industrial density, type of industry, location of the sample point in relation to the street corner, treeless condition, and topographic level. Dried weight/fresh weight ratio (DW/FW) and specific leaf area (SLA) were calculated, and concentrations of chlorophylls, carotenoids, total sulfur, soluble proteins, malondialdehyde (MDA), and hydroperoxy conjugated dienes (HPCD) were determined in leaf samples. Sulfur content correlates positively with traffic density and SLA correlates negatively with some combinations of the categorical variables; MDA correlates positively with topographic level and total protein concentration correlates negatively with treeless condition. On the basis of our results, traffic, location of trees, type of industry, situation of a tree with respect to others, and topographic level are the environmental variables to bear in mind when selecting analogous sampling points in a passive monitoring program. An approximation to predict tree injury may be obtained by measuring DW/FW ratio, proteins, pigments, HPCD, and MDA as they are responsible for the major variability of data.     

草原旅游发展中旅游管理部门环境意识的调查研究

根据环境意识结构．设计了旅游管理部门环境意识调查问卷。其主要的指标体系包括：旅游环境知识水平、旅游环境态度、旅游环境评价和旅游环境行为四个方面。对指标体系各部分之间以及每一指标部分的每一题目之间的相对重要性进行权重的确定．而且对各部分的每道题目的各个选项予以赋分。基于权重和赋分．结合调查问卷的实际情况，设计了指标体系各部分评价模型和环境意识总体评价模型。以此来计算草原旅游发展中旅游管理部门环境意识水平的综合得分。经过分析得知，旅游管理部门环境意识模式是“环境知识制约型”模式。     

三江平原地貌因子及其主要环境地质问题

地貌因子有其不可替代的作用和功能,是决定环境的主要因子,是生态地质环境中最积极最活跃的主导支力条件;是生态平衡的重中之重;是生态地质环境的基础,并影响其它因子或成份.如地貌因子或成份发生了变化,其它因子或成份就会发生一系列连锁反应;地貌因子发生变化或失去平衡,其它因子也会发生变化或失去平衡.文本论述了三江平原地貌特征,详细地分析了地貌的作用,阐明了有关地貌的主要环境地质问题.     

The evolution of sustainability

Six separate but related strains of thought have emerged prominently since 1950 in discussions of such phenomena as the interrelationships among rates of population growth, resource use, and pressure on the environment. They are the ecological/carrying capacity root, the resources/environment root, the biosphere root, the critique of technology root, the no growth/slow growth root, and the ecodevelopment root.Each of these strains of thought was fully developed before the word sustainable itself was used. Many of the roots are based on fundamentally opposing assessments of the future of mankind. Many of the roots, such as the ecology/carrying capacity root, are based on physical concepts, and they exclude normative values. Others, such as the ecodevelopment root, include such values as equity, broad participation in governance, and decentralized government.When the word sustainability was first used in 1972 in the context of man's future, in a British book,Blueprint for Survival, normative concepts were prominent. This continued to be the case when the word was first used in 1974 in the United States to justify a no growth economy.Sustainability was first used in a United Nations document in 1978. Normative concepts, encapsulated in the term ecodevelopment, were prominent in the United Nations publications.After about 1978, the term sustainability began to be used not only in technological articles and reports but also in policy documents culminating in the use of the term in the report of the summit meeting of the Group of Seven in 1989.The roots of the term sustainability are so deeply embedded in fundamentally different concepts, each of which has valid claims to validity, that a search for a single definition seems futile. The existence of multiple meaning is tolerable if each analyst describes clearly what he means by sustainability.     

基于遥感尾气监测的柴油车气态污染物排放因子计算方法研究

采用遥感尾气测试系统实测了柴油车在实际道路工况下的CO、HC和NO排放特征,修正了排放因子的计算方法,并与车载排放测试系统（PEMS）实测结果进行了验证,获得了实测车辆的CO、HC和NO排放因子.测试结果显示,在各种遥感监测的工况下柴油车尾气中均含有较高浓度的氧气,未考虑氧气影响的燃烧方程反演获得的各污染物体积浓度计算值与PEMS实测值的偏差较大,且氧气浓度越大,偏差越大.经过氧气修正的燃烧方程反演计算的尾气浓度与PEMS实测值吻合度大幅提升,适用于实际工况下遥感检测车辆尾气的反演计算.修正算法得到CO、HC和NO的排放因子离散性较小,精确度较高,可以为量化柴油车尾气排放贡献提供科学依据.     

全球液化石油气运输网络贸易社区特征及其演化分析

液化石油气在全球清洁能源消耗市场中扮演着极为重要的角色,其通过船舶在不同港口之间进行运输,而港口之间通过局部密集的运输关系,形成了联系极为紧密的贸易社区。采用复杂网络社区探测方法,基于2013—2017年全球液化石油气船舶轨迹大数据构建运输网络,并对其贸易社区特征及其演化趋势开展分析。结果表明：（1）液化石油气（Liquefied Petroleum Gas,LPG）贸易社区内的港口之间的联系更加紧密,不同社区内的枢纽港口联系也日益紧密;（2）各个贸易社区的规模呈现出增长趋势,且同一社区内的港口在地理空间上变得更为集聚;（3）亚太地区、中东、西北欧和地中海地区形成的社区在全球LPG贸易中一直保持着重要地位,而随着时间推移,美洲社区已逐渐从一个相对孤立的社区发展成为与其他社区存在紧密联系的社区。     

基于网络数据的乡村旅游热点识别及成因分析——以江苏省为例

基于旅游网站数据,提出一种乡村旅游热点识别方法,以江苏省为例,运用趋势面、核密度、热点分析等方法探寻乡村旅游冷热格局及演变特征,并借助地理探测器揭示其时空演化的影响因素。结果表明：（1）江苏省乡村旅游热度的时间演化规律明显,年际变化呈“S”型演变轨迹;季节变化呈“三峰四谷”特征。（2）江苏省乡村旅游热度的空间结构在2009—2017年间经历了“单核—双核—三核”的演化过程,但其空间异质性依然显著,整体表现为“南高北低,东高西低”的差异特征。（3）影响因素在不同时段的影响强度各异,交通条件、服务能力一直是主导因素,经济水平对乡村旅游发展早期的热度提升有显著影响,资源禀赋的显著性趋于下降,生态环境和政府导向的影响力逐渐增强。基于网络数据的乡村旅游热点识别为乡村旅游定量研究提供了新的研究视角,对乡村旅游资源开发与区域合作具有重要的指导意义。