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     

Fluctuations of Population Size and Structure in the Northern Mole Vole: Preliminary Analysis

Long-term stationary studies on the ecology of the northern mole vole (Ellobius talpinus Pall.), performed by the mark–recapture method from 1985 to 1997, have provided original data on population dynamics and structure. The analysis shows that, to reveal cyclic fluctuations of population size in this species, the period of three years should be taken as a unit of time for estimating the duration of one phase. The 12-year population cycle in E. talpinus has four distinct phases: an increase, a peak, a decline, and a minimum. At each phase, the population is characterized by certain features of family structure, age composition, birth and death rates, and the composition of migrants.     

成都市大气颗粒物粒径分布及其对能见度的影响

使用环境颗粒物分析仪（GRIMM180）对成都市2018年10月—2019年9月0.25~32 μm的大气颗粒物数浓度粒径分布进行观测,结合细颗粒物（PM_2.5）质量浓度以及相对湿度（RH）、能见度、降水量等气象要素数据,分析了成都市大气颗粒物粒径分布及其与能见度的关系.结果表明,观测期间成都市大气颗粒物以细粒子为主,0.25~0.5 μm的粒子数浓度占总数浓度的97.75%,数浓度谱呈单峰分布,2018年秋季、2019年夏季表面积谱呈双峰分布,2018年冬季、2019年春季表面积谱呈三峰,体积谱均为三峰分布;在不同RH区间,PM_2.5质量浓度及数浓度均与能见度呈负相关,且其中0.25~0.5 μm粒径段的细颗粒物因为对可见光波段的米散射效应而对能见度产生较大影响;在不同RH情况下,不同粒径段颗粒物数浓度对能见度的影响程度有所差别：在低RH（<70%）下,0.25~0.3 μm粒径段粒子数浓度对能见度影响最大;在中等RH（70%~80%）下,0.3~0.5 μm粒径段粒子数浓度对能见度的影响最大;而在高RH（>80%）下,0.3~0.5 μm和0.5~1 μm粒径段粒子数浓度对能见度影响相当.     

雨水管道沉积物中典型无机氮的干期粒径分布

以南京江北新区分流制雨水管道沉积物为研究对象,考察不同粒径沉积物中铵态氮（NH₃-N）和硝态氮（NO₃^--N）干期分布特征,分析其随干期长度的变化关系,并探讨沉积物理化性质及微生物菌群结构对NH₃-N和NO₃^--N干期分布的影响.结果表明：粒径≤0.075mm的沉积物中NH₃-N占比最高（交通区30.8%,商业区36.7%）;交通区粒径≤0.075mm的沉积物中NO₃^--N占比最高（33.0%）,而商业区粒径0.075~0.15mm沉积物中NO₃^--N占比最高（34.4%）;干期长度与交通区0.075~0.15mm粒径段的沉积物中NO₃^--N含量及商业区粒径≥0.3mm的沉积物中NH₃-N含量之间的相关性均最显著;雨水管道沉积物中NH₃-N和NO₃^--N的干期分布与O-H和N-H等官能团、表面极性和亲水性、微观形貌等有一定关联;交通区雨水管道沉积物中Gemmobacter等反硝化优势菌种（相对丰度总和为20.15%）对NO₃^--N干期分布影响更显著.     

海绵城市地块汇水区颗粒污染物的传输

目前我国海绵工程建设多集中在地块汇水区单元内开展,通过多个低影响开发(LID)设施协同完成地表径流水质水量的调控,但基于地块汇水区尺度下城市面源污染的产生和控制效果鲜有报道.本研究比较分析了不同硬化率地块汇水单元内的面源颗粒污染物晴天累积、降雨冲刷、地表径流及径流输出负荷状况.结果表明,地块汇水单元内硬质路面是面源颗粒污染物贡献的最主要的下垫面类型,中硬化率(61.1%)地块和高硬化率(73.6%)地块路面街尘累积量分别约占汇水区单元的88.4%(2.22～12.51 g·m~(-2))和90.1%(4.99～33.43 g·m~(-2)),对径流SS的输出贡献比率分别约为91.7%(0.97～7.34 g·m~(-2))和90.5%(0.92～18.77 g·m~(-2)),降雨径流SS污染负荷占比分别约为95.2%和83.1%,经LID设施处理后输出径流污染负荷约为地表径流的24.0%和40.2%.硬质路面的街尘晴天累积及降雨冲刷以150μm为主,地表径流及输出径流则以50μm粒径段为主,同时地块不透水比例的增加,细粒径(105μm)颗粒物的累积及冲刷分布增大(24.4%和106.4%),而粒径50μm的颗粒物在路面径流中的分布减小(12.4%).屋面的街尘累积、冲刷及降雨径流的粒径分布状况与硬质路面大致相似,但中硬化率地块(1 000μm)和高硬化率地块(250～450μm、45μm)在3个粒径段范围的颗粒物累积和冲刷相较于路面街尘粒径分布明显增加(1 000μm:58.1%和108.5%; 250～450μm:72.9%和41.8%;45μm:59.2%和64.8%).以上结果揭示了颗粒污染物在地块汇水区尺度下的污染全过程(累积-冲刷-输出)分布及LID设施对地块整体SS污染负荷的控制效果,可为地块汇水单元内LID设施工程绩效的科学评估提供重要参考.     

生物基聚合物PHBV和PLA复合材料在不同介质中的生物降解及其影响因素

传统工艺的塑料生产不仅依赖石油资源的持续开发利用,同时给环境造成了前所未有的压力,近年来生物基聚合物（聚（3-羟基-3-戊酸酯）-PHBV,聚乳酸-PLA）日渐成为传统石油基塑料的替代产品.本文采用呼吸测试手段,旨在揭示均质复合材料在不同环境介质（土壤、熟化堆肥、水体）条件下及有机添加剂（木质素）,无机添加剂（蒙脱石）和天然有机物链增长剂（Joncryl）作用下的生物降解特征.结果表明：当链增长剂Joncryl添加量为5%时,对所有介质PHBV和PLA复合材料产生显著抑制作用.Joncryl添加量为0.2%时,未对所测样品的生物降解行为产生干扰作用.在熟化堆肥介质中,PLA复合材料比PHBV基质混合物的生物降解速率明显降低.有机木质纤维添加剂（榛子壳粉末）单独在聚合物中添加或者和链增长剂Joncryl以及非有机添加剂（Dellite72T）共同作用下都可促进PLA聚合物中各组分的相容连接性.实验结果表明,新型添加剂在不同介质中以二元或三元添加的方式对生物降解过程产生重要影响,该研究将为新型材料使用后的生物降解效应提供理论依据.     

滤纸法测定悬浮物的干扰及其消除

提出了滤纸法测定悬浮物时，水样的酸碱度，取样量的多少对悬浮物测定有直接的影响。通过实验验证，对于偏酸，偏碱的水样用酸碱中和后再过滤即可消除影响，取样量应根据悬浮物的不同而定。     

Large pore size polyacrylonitrile membrane for ultrafiltration

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介质粒径对复三维电极-生物膜脱硝反应器的影响

研究了无烟煤作填充介质时其粒径对复三维电极 生物膜反应器脱硝效果的影响 .选择了两种具有代表性的无烟煤粒径 :平均粒径D分别为 1 9mm和 4 0mm .研究了两种粒径介质的反应器出水中的NO-3 N、NO-2 N、pH变化 ,并对电流效率及处理负荷进行了对比 .结果表明在一定电流下 ,两反应器的NO-3 N去除率均能达到 98%;在同样操作条件下 ,D为 1 9mm反应器的脱硝能力优于D为 4 0mm反应器 ,前者比后者对水中NO-3 N的去除率高 10 %左右 .D为 1 9mm反应器的NO-3 N最高容积负荷、NO-3 N最高电极负荷、电流效率分别为 0 0 15kg (m3 ·h)、0 0 37mg (cm2 ·h)、36 0 %,均高于D为 4 0mm反应器约 10 %.以小粒径无烟煤为介质的反应器的生物量明显高于大粒径介质反应器 .