人类活动对锡林郭勒盟草原净初级生产力的影响研究

净初级生产力是草地生态系统生产能力的体现,同时也是草地生态系统固碳能力的重要指标。论文利用MOD17A3净初级生产力数据（NPP）与气象资料,分析了2001—2010年人类活动对锡林郭勒盟草原净初级生产力的影响。研究表明：1）锡林郭勒盟草原实际净初级生产力（NPP_A）介于41.32~362.27 g C·m^-2·a^-1,均值为150.78 g C·m^-2·a^-1,有较明显的水平地带性规律,由东向西逐渐减小,草甸草原最大,典型草原次之,荒漠草原最小;2）锡林郭勒盟草原人类活动影响的净初级生产力（NPP_H）介于-185.07~153.92 g C·m^-2·a^-1,均值为-34.80 g C·m^-2·a^-1,人类活动负作用占草原总面积的93.4%,人类活动正作用仅占6.6%;3）人类活动对锡林郭勒盟草原净初级生产力的影响主要是由负作用向正作用转变,且空间分布有明显的南北界线,南部表现为负作用增强,北部为正作用增强。研究可为锡林郭勒盟草地资源的管理和可持续利用提供参考依据。     

磷酸三(1,3-二氯-2-丙基)酯对L-02肝细胞氧化应激及凋亡损伤机制

在各类环境介质及生物体甚至人体中都检测到有机磷阻燃剂磷酸三(1,3-二氯-2-丙基)酯(tris(1,3-dichloro-2-propyl)phosphate,TDCPP)的存在,为探究TDCPP对人体健康的毒性作用,选取人体正常肝细胞L-02细胞作为模型,考察在体外暴露条件下TDCPP对L-02细胞的细胞存活率、凋亡、氧化应激以及p53通路相关基因方面的影响。MTT结果显示,24 h、48 h、72h的半数致死浓度(LC50)分别为:116.56μmol·L~(-1)、81.89μmol·L~(-1)、65.11μmol·L~(-1)。TDCPP暴露24 h条件下,随着TDCPP暴露浓度的增加,细胞的凋亡率和活性氧(reactive oxygen species,ROS)水平也逐渐增加,100μmol·L~(-1)浓度条件下凋亡高达25.58%±1.61%,ROS水平是对照组的2.07±0.07倍。实时荧光定量PCR法检测线粒体凋亡通路相关基因的表达情况,在TDCPP刺激下,Bax、caspase-3、caspase-9、p53和Apaf-1相对表达量增加,Bcl-2相对表达量减少。蛋白免疫印迹法检测发现Bax/Bcl-2和caspase-3均随浓度增加而递增。本研究为综合评估TDCPP的生物和环境健康毒理效应提供了实验数据及理论支持。     

广州市居民食品砷摄入的健康风险评价

从暴露途径来看,食物是人体砷暴露的主要途径之一。从饮食结构来看,广州市居民膳食主要来源于谷类食品,同时鱼虾类总体平均摄入量约为全国总体平均摄入量的2倍。因此,在分析广州市市场大米和海鲜这2种典型食品中砷含量的基础上对广州市居民食品砷摄入的健康风险进行了评价。分析了广州市场上的26种不同品牌的大米中的总砷含量,其含量范围为0.082～0.171μg·g~(-1),平均浓度为(0.127±0.027)μg·g~(-1),满足绿色食品大米标准(≤0.40μg·g~(-1))。在14种鱼虾蟹贝类海鲜中的砷含量分析基础上,计算得出广州市场上鱼类中总砷的平均含量为0.488μg·g~(-1),虾蟹贝类中总砷的平均含量为3.44μg·g~(-1),相比较国内外,广州市场鱼虾蟹中砷的含量整体处于中间水平。最后综合文献调研中其他主要食品中砷的含量,计算得出广州市成人通过食品每日摄入总砷的量为5.08μg·kg~(-1)BW·d~(-1)。建议日常饮食需要特别控制每日海鲜的摄入量,尤其是砷含量较高的濑尿虾、红虾及红蟹、花蟹。     

Evaluating the social and ecological effectiveness of partially protected marine areas

Marine protected areas (MPAs) are a primary tool for the stewardship, conservation, and restoration of marine ecosystems, yet 69% of global MPAs are only partially protected (i.e., are open to some form of fishing). Although fully protected areas have well-documented outcomes, including increased fish diversity and biomass, the effectiveness of partially protected areas is contested. Partially protected areas may provide benefits in some contexts and may be warranted for social reasons, yet social outcomes often depend on MPAs achieving their ecological goals to distinguish them from open areas and justify the cost of protection. We assessed the social perceptions and ecological effectiveness of 18 partially protected areas and 19 fully protected areas compared with 19 open areas along 7000 km of coast of southern Australia. We used mixed methods, gathering data via semistructured interviews, site surveys, and Reef Life (underwater visual census) surveys. We analyzed qualitative data in accordance with grounded theory and quantitative data with multivariate and univariate linear mixed-effects models. We found no social or ecological benefits for partially protected areas relative to open areas in our study. Partially protected areas had no more fish, invertebrates, or algae than open areas; were poorly understood by coastal users; were not more attractive than open areas; and were not perceived to have better marine life than open areas. These findings provide an important counterpoint to some large-scale meta-analyses that conclude partially protected areas can be ecologically effective but that draw this conclusion based on narrower measures. We argue that partially protected areas act as red herrings in marine conservation because they create an illusion of protection and consume scarce conservation resources yet provide little or no social or ecological gain over open areas. Fully protected areas, by contrast, have more fish species and biomass and are well understood, supported, and valued by the public. They are perceived to have better marine life and be improving over time in keeping with actual ecological results. Conservation outcomes can be improved by upgrading partially protected areas to higher levels of protection including conversion to fully protected areas.     

Modeling scale up of anthropogenic impacts from individual pollinator behavior to pollination systems

Understanding how anthropogenic disturbances affect plant–pollinator systems has important implications for the conservation of biodiversity and ecosystem functioning. Previous laboratory studies show that pesticides and pathogens, which have been implicated in the rapid global decline of pollinators over recent years, can impair behavioral processes needed for pollinators to adaptively exploit floral resources and effectively transfer pollen among plants. However, the potential for these sublethal stressor effects on pollinator–plant interactions at the individual level to scale up into changes to the dynamics of wild plant and pollinator populations at the system level remains unclear. We developed an empirically parameterized agent-based model of a bumblebee pollination system called SimBee to test for effects of stressor-induced decreases in the memory capacity and information processing speed of individual foragers on bee abundance (scenario 1), plant diversity (scenario 2), and bee–plant system stability (scenario 3) over 20 virtual seasons. Modeling of a simple pollination network of a bumblebee and four co-flowering bee-pollinated plant species indicated that bee decline and plant species extinction events could occur when only 25% of the forager population showed cognitive impairment. Higher percentages of impairment caused 50% bee loss in just five virtual seasons and system-wide extinction events in less than 20 virtual seasons under some conditions. Plant species extinctions occurred regardless of bee population size, indicating that stressor-induced changes to pollinator behavior alone could drive species loss from plant communities. These findings indicate that sublethal stressor effects on pollinator behavioral mechanisms, although seemingly insignificant at the level of individuals, have the cumulative potential in principle to degrade plant–pollinator species interactions at the system level. Our work highlights the importance of an agent-based modeling approach for the identification and mitigation of anthropogenic impacts on plant–pollinator systems.     

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.     

Exploring human–nature interactions in national parks with social media photographs and computer vision

Understanding the activities and preferences of visitors is crucial for managing protected areas and planning conservation strategies. Conservation culturomics promotes the use of user-generated online content in conservation science. Geotagged social media content is a unique source of in situ information on human presence and activities in nature. Photographs posted on social media platforms are a promising source of information, but analyzing large volumes of photographs manually remains laborious. We examined the application of state-of-the-art computer-vision methods to studying human–nature interactions. We used semantic clustering, scene classification, and object detection to automatically analyze photographs taken in Finnish national parks by domestic and international visitors. Our results showed that human–nature interactions can be extracted from user-generated photographs with computer vision. The different methods complemented each other by revealing broad visual themes related to level of the data set, landscape photogeneity, and human activities. Geotagged photographs revealed distinct regional profiles for national parks (e.g., preferences in landscapes and activities), which are potentially useful in park management. Photographic content differed between domestic and international visitors, which indicates differences in activities and preferences. Information extracted automatically from photographs can help identify preferences among diverse visitor groups, which can be used to create profiles of national parks for conservation marketing and to support conservation strategies that rely on public acceptance. The application of computer-vision methods to automatic content analysis of photographs should be explored further in conservation culturomics, particularly in combination with rich metadata available on social media platforms.     

Digital data sources and methods for conservation culturomics

Ongoing loss of biological diversity is primarily the result of unsustainable human behavior. Thus, the long-term success of biodiversity conservation depends on a thorough understanding of human–nature interactions. Such interactions are ubiquitous but vary greatly in time and space and are difficult to monitor efficiently at large spatial scales. However, the Information Age also provides new opportunities to better understand human–nature interactions because many aspects of daily life are recorded in a variety of digital formats. The emerging field of conservation culturomics aims to take advantage of digital data sources and methods to study human–nature interactions and thus to provide new tools for studying conservation at relevant temporal and spatial scales. Nevertheless, technical challenges associated with the identification, access, and analysis of relevant data hamper the wider adoption of culturomics methods. To help overcome these barriers, we propose a conservation culturomics research framework that addresses data acquisition, analysis, and inherent biases. The main sources of culturomic data include web pages, social media, and other digital platforms from which metrics of content and engagement can be obtained. Obtaining raw data from these platforms is usually desirable but requires careful consideration of how to access, store, and prepare the data for analysis. Methods for data analysis include network approaches to explore connections between topics, time-series analysis for temporal data, and spatial modeling to highlight spatial patterns. Outstanding challenges associated with culturomics research include issues of interdisciplinarity, ethics, data biases, and validation. The practical guidance we offer will help conservation researchers and practitioners identify and obtain the necessary data and carry out appropriate analyses for their specific questions, thus facilitating the wider adoption of culturomics approaches for conservation applications.     

广州地区室内灰尘中典型非邻苯增塑剂的污染特征与暴露风险

非邻-苯二甲酸酯增塑剂作为邻-苯二甲酸酯的替代物被广泛用于生产和生活用品中,但目前对其环境存在和人体暴露风险知之甚少.为研究室内环境的污染状况及人体暴露,分析了广州市83户住宅灰尘中12种典型非邻苯增塑剂.结果表明,对-苯二甲酸二辛酯（DEHT）、偏苯三酸三辛酯（TOTM）、乙酰柠檬酸三丁酯（ATBC）、己二酸庚基壬基酯、己二酸二（2-乙基己基）酯和偏苯三酸三辛烷基酯100%检出.非邻-苯二甲酸酯增塑剂总含量中值为101 μg·g^-1,含量范围为22.4~615 μg·g^-1.DEHT的含量最高（含量范围9~487 μg·g^-1）,其次是TOTM （含量范围0.3~87 μg·g^-1）和ATBC （含量范围1.7~50 μg·g^-1）.通过暴露模型评估了成人与儿童经灰尘摄食的日暴露量,其中儿童摄入的非邻苯增塑剂总日暴露量为367 ng·（kg·d）^-1,是成人日暴露量43 ng·（kg·d）^-1的8~9倍.进一步通过危险商对暴露量进行风险评价,结果表明成人和儿童经灰尘摄食对非邻苯增塑剂的暴露风险均处于可接受范围.     

COVID-19疫情期间京津冀大气污染物变化及影响因素分析

为了应对COVID-19疫情,京津冀地区采取了一系列严格的管控措施,这些措施导致了大气污染物人为源排量的减少,为探究大气污染受人类活动的影响程度提供了时机.将疫情防控分为前期、初期、中期和后期这4个阶段,并结合气象、交通量和工业数据,综合运用数理统计和空间分析方法,得出各时间段大气污染物的变化情况及影响因素,为京津冀地区进一步治理大气污染提出了合理化建议.结果表明：①京津冀三地在疫情防控期总体的AQI值和6项污染物同比2019年均有下降,其中SO₂、PM₁₀和NO₂的降幅较大（分别为26.5%、24.3%和16.9%）;由初期到后期,各污染物（除O₃）总体处于下降趋势;O₃在初期增幅大（76.2%）,中后期增幅放缓.②防控初期北京市的重污染天气是污染物本地积累、二次转化和区域传输共同作用的结果;北京2月份的PM_2.5浓度同比相似气象条件下的2014年2月偏低近6成;若仅考虑人为减排的影响,则各污染物浓度同比2019年均有下降.③防控中后期,随着交通量和工业复工率进一步扩大,各污染物变化趋于平稳或有微升;重工业城市的热异常辐射强度与主要污染物的灰色关联度大于0.6,即控制工业排量仍是治理大气污染的关键.