A generalized approach for producing,quantifying, and validating citizen science data from wildlife images

Citizen science has the potential to expand the scope and scale of research in ecology and conservation, but many professional researchers remain skeptical of data produced by nonexperts. We devised an approach for producing accurate, reliable data from untrained, nonexpert volunteers. On the citizen science website www.snapshotserengeti.org , more than 28,000 volunteers classified 1.51 million images taken in a large‐scale camera‐trap survey in Serengeti National Park, Tanzania. Each image was circulated to, on average, 27 volunteers, and their classifications were aggregated using a simple plurality algorithm. We validated the aggregated answers against a data set of 3829 images verified by experts and calculated 3 certainty metrics—level of agreement among classifications (evenness), fraction of classifications supporting the aggregated answer (fraction support), and fraction of classifiers who reported “nothing here” for an image that was ultimately classified as containing an animal (fraction blank)—to measure confidence that an aggregated answer was correct. Overall, aggregated volunteer answers agreed with the expert‐verified data on 98% of images, but accuracy differed by species commonness such that rare species had higher rates of false positives and false negatives. Easily calculated analysis of variance and post‐hoc Tukey tests indicated that the certainty metrics were significant indicators of whether each image was correctly classified or classifiable. Thus, the certainty metrics can be used to identify images for expert review. Bootstrapping analyses further indicated that 90% of images were correctly classified with just 5 volunteers per image. Species classifications based on the plurality vote of multiple citizen scientists can provide a reliable foundation for large‐scale monitoring of African wildlife.     

Characterizing Spatial Uncertainty when Integrating Social Data in Conservation Planning

Recent conservation planning studies have presented approaches for integrating spatially referenced social (SRS) data with a view to improving the feasibility of conservation action. We reviewed the growing conservation literature on SRS data, focusing on elicited or stated preferences derived through social survey methods such as choice experiments and public participation geographic information systems. Elicited SRS data includes the spatial distribution of willingness to sell, willingness to pay, willingness to act, and assessments of social and cultural values. We developed a typology for assessing elicited SRS data uncertainty which describes how social survey uncertainty propagates when projected spatially and the importance of accounting for spatial uncertainty such as scale effects and data quality. These uncertainties will propagate when elicited SRS data is integrated with biophysical data for conservation planning and may have important consequences for assessing the feasibility of conservation actions. To explore this issue further, we conducted a systematic review of the elicited SRS data literature. We found that social survey uncertainty was commonly tested for, but that these uncertainties were ignored when projected spatially. Based on these results we developed a framework which will help researchers and practitioners estimate social survey uncertainty and use these quantitative estimates to systematically address uncertainty within an analysis. This is important when using SRS data in conservation applications because decisions need to be made irrespective of data quality and well characterized uncertainty can be incorporated into decision theoretic approaches.     

基于RBI与多米诺效应的输气站场设备定量风险评价

针对目前输气站场设备风险评价方法仅以单个设备为评价对象,并未考虑设备间相互影响的特点,提出将多米诺效应分析引入输气站场设备风险评价当中,再结合RBI(基于风险检测方法)对输气站场设备进行定量风险评价。首先,计算所评价设备的失效概率与危险指数,得到设备固有风险;然后对设备的多米诺效应风险进行计算;最后,得到设备总风险。实例分析表明,考虑多米诺效应风险后,站场单个设备的风险要明显增大。     

基于HJ-1B与TM热红外数据的大亚湾核电基地温排水遥感监测

选取同天过境的Landsat5TM和HJ-1B红外相机数据,在获取3个大气参数后,结合辐射传输模型分别对大亚湾核电基地附近海域海表温度和温排水温升区的分布情况进行遥感监测,对比结果显示,环境卫星遥感监测数据与TM数据监测所得温排水在空间分布上具有较高一致性,二者反演出的绝对温度相差不超过1.1℃,相同温升等级范围内的相对温度均值也不超过0.4℃.因此,HJ-1B红外相机可满足核电站热污染的监测需求.     

DNAPL在透镜体及表面活性剂作用下的运移研究

选择四氯乙烯(PCE)作为典型重非水相液体(DNAPLs)污染物,进行PCE在二维砂箱中的运移及修复实验,采用一种改进光透法探讨DNAPL在含不同透镜体非均质含水层中的运移和饱和度分布特性.在此基础上,考察非离子表面活性剂(吐温80)对DNAPL的原位冲洗修复效果.结果表明,在模拟天然地下水流条件下,当PCE运移到达各透镜体时,PCE均未进入透镜体而是在其上方聚集形成污染池,然后逐渐侧向扩散,即使在较粗透镜体(20/30目和40/60目石英砂按 1:1质量比例混合)上也无法进入.吐温80对PCE的修复效果显著,冲洗58h后,94.2%的PCE被去除.表面活性剂的引入能够减小PCE和水的界面张力,界面张力的减小量可达38.8dyn/cm,相应各透镜体上覆界面处的毛细压力水头值会有不同程度的减小,在较粗透镜体上的PCE可以穿透透镜体并继续向下运移.透镜体的毛细截留作用会限制修复后期的修复效率,修复75,3520min的修复效率分别为0.63,0.05g/g,其中较粗透镜体上截留的PCE相对其他较细透镜体容易移出.     

人工神经网络模型在水质预警中的应用研究进展

水质预警模型是大数据时代构建环境智能决策与管理体系的关键技术.近年来,水质自动化监测能力的提升以及测管协同对环境模型的强烈需求,激发了研究人员探索新的建模方法并努力提高模型预测性能.其中,人工神经网络(Artificial Neural Network, ANN)模型发展迅速.本文综述了3大类ANN模型的发展历史和模型结构特点,梳理了ANN模型在水质数据软测量、数据异常检测和时间序列预测等方面的研究进展,归纳了一般建模流程、技术建议和常用的模型性能指标,发现ANN模型的应用依赖于监测数据质量,存在模型可解释性差、模型运行硬件资源要求较高等不足,提出未来水质预警模型的研发思路和重点,需要加快推进水环境监测技术与预警模型的协同发展和业务化应用,通过多种应用场景检验实现技术迭代,形成大数据驱动的水质在线监测-智能预警-应急管理支撑体系,助力我国环境治理能力现代化.     

Adapting to new policy environment – past pattern and future trend in us-sino waste plastic trade flow

Plastics are one of the most used materials in human activities, where consumer consumption and industrial production together has imposed vast rise in demand for this material in last century. While plastic is ideally derived from crude oil as a primary source from manufacturers’ perspective, varying crude oil prices are driving manufacturers economically to seek for alternative sources for plastics production. Waste plastic recovered from obsolete consumer products thus becomes an economic substitution for virgin plastics, which is further intensified with the possibility of international waste plastic trading. This study focuses on waste plastic trade between the US and mainland China by performing a correlation analysis of trade data. It is suggested in this study that although waste plastics are traded from the US to mainland China in general, as many of us believes, the route is gradually shifting in the past years. With tightening Chinese customs regulations, waste plastic from the US now tends to take a transit in a third destination (Hong Kong SAR for instance) for preliminary treatment to bypass Chinese customs inspection. Such phenomenon is worth noting, as a complication in waste plastic trading route hinders waste plastic transboundary movement monitoring. Furthermore, it will have adverse consequent consumer, industrial, and environmental impacts. It is thus necessary for national competent authorities to strengthen cooperative study and communication capacity in the future as a response to the changing waste plastic trade pattern.     

京津冀一次污染过程的星地同步动态监测分析

京津冀地区大气污染监管逐渐走向区域联防联控模式,卫星遥感可实现大范围实时动态监测,地基监测能够获取精细的网点信息.结合卫星和地基数据,可对区域污染的生消过程进行三维立体的跟踪.本文通过综合分析卫星遥感数据、地面PM_(2.5)浓度数据、激光雷达垂直污染监测数据以及气象数据,分析了2018年3月8～10日京津冀区域污染的形成过程、传输路径、影响范围以及气象因子变化.结果发现,本次污染覆盖范围面积达20万km~2左右,区域内以四级中度污染为主,区域间的污染传输过程非常典型. 3月8～9日北京-保定偏南风频率为50%左右,冀南部分地区到达100%,在持续偏南风作用下,北京-保定一带空气质量由一级优迅速升至四级轻度污染,气溶胶光学厚度高值区由京津冀南部的邯郸-邢台西部山前推至北部燕山前. 3月10日该区域转以弱偏北风为主,湿度明显升高,京津冀南部形成污染辐合,污染重心南移至邯郸-邢台东部;午后,北京转偏东风,空气质量由东向西递次转好.从激光雷达垂直观测结果看,重污染期间北京地区污染层主要出现在1 000 m以下.近地面800 m以下,1 200～1 500 m多次出现双逆温层,且逆温强度高达4～7℃,非常不利于污染物垂直扩散.由此可见,在区域能源消耗和污染排放量依旧很大的背景下,一旦气象条件转差,很容易形成区域性重污染.     

How to address data privacy concerns when using social media data in conservation science

Social media data are being increasingly used in conservation science to study human–nature interactions. User-generated content, such as images, video, text, and audio, and the associated metadata can be used to assess such interactions. A number of social media platforms provide free access to user-generated social media content. However, similar to any research involving people, scientific investigations based on social media data require compliance with highest standards of data privacy and data protection, even when data are publicly available. Should social media data be misused, the risks to individual users' privacy and well-being can be substantial. We investigated the legal basis for using social media data while ensuring data subjects’ rights through a case study based on the European Union's General Data Protection Regulation. The risks associated with using social media data in research include accidental and purposeful misidentification that has the potential to cause psychological or physical harm to an identified person. To collect, store, protect, share, and manage social media data in a way that prevents potential risks to users involved, one should minimize data, anonymize data, and follow strict data management procedure. Risk-based approaches, such as a data privacy impact assessment, can be used to identify and minimize privacy risks to social media users, to demonstrate accountability and to comply with data protection legislation. We recommend that conservation scientists carefully consider our recommendations in devising their research objectives so as to facilitate responsible use of social media data in conservation science research, for example, in conservation culturomics and investigations of illegal wildlife trade online.     

永久基本农田保护的实施评价与政策启示--以我国东部地区XX地级市为例

基于“三调”数据分析我国东部地区XX地级市永久基本农田保护变化,从流失去向与流失空间分布两个方面深入分析了其真实境况,从而提出切实的保护政策建议。结果表明:①流失去向包括农业结构调整、建设占用和自然损毁,其中农业结构调整占用为主导。②城市圈内比圈外占用普遍严重,尤其是城乡建设占用了大量基本农田。③永久基本农田存在空间错配现象,未做到“应划尽划”。据此,提出构建农户补偿机制、县级保护任务量与存量建设指标相挂钩、协同基本农田—生态—城镇空间布局,实施圈内基本农田动态监测机制等系列措施,以提升保护效果。