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.     

Trends in Deforestation and Forest Degradation after a Decade of Monitoring in the Monarch Butterfly Biosphere Reserve in Mexico

We used aerial photographs, satellite images, and field surveys to monitor forest cover in the core zones of the Monarch Butterfly Biosphere Reserve in Mexico from 2001 to 2012. We used our data to assess the effectiveness of conservation actions that involved local, state, and federal authorities and community members (e.g., local landowners and private and civil organizations) in one of the world's most iconic protected areas. From 2001 through 2012, 1254 ha were deforested (i.e., cleared areas had <10% canopy cover), 925 ha were degraded (i.e., areas for which canopy forest decreased), and 122 ha were affected by climatic conditions. Of the total 2179 ha of affected area, 2057 ha were affected by illegal logging: 1503 ha by large‐scale logging and 554 ha by small‐scale logging. Mexican authorities effectively enforced efforts to protect the monarch reserve, particularly from 2007 to 2012. Those efforts, together with the decade‐long financial support from Mexican and international philanthropists and businesses to create local alternative‐income generation and employment, resulted in the decrease of large‐scale illegal logging from 731 ha affected in 2005–2007 to none affected in 2012, although small‐scale logging is of growing concern. However, dire regional social and economic problems remain, and they must be addressed to ensure the reserve's long‐term conservation. The monarch butterfly (Danaus plexippus) overwintering colonies in Mexico—which engage in one of the longest known insect migrations—are threatened by deforestation, and a multistakeholder, regional, sustainable‐development strategy is needed to protect the reserve. Tendencias en la Deforestación y la Degradación de Forestal después de una Década de Monitoreo en la Reserva de la Biósfera de la Mariposa Monarca en México     

Foundations of Resilience Thinking

Through 3 broad and interconnected streams of thought, resilience thinking has influenced the science of ecology and natural resource management by generating new multidisciplinary approaches to environmental problem solving. Resilience science, adaptive management (AM), and ecological policy design (EPD) contributed to an internationally unified paradigm built around the realization that change is inevitable and that science and management must approach the world with this assumption, rather than one of stability. Resilience thinking treats actions as experiments to be learned from, rather than intellectual propositions to be defended or mistakes to be ignored. It asks what is novel and innovative and strives to capture the overall behavior of a system, rather than seeking static, precise outcomes from discrete action steps. Understanding the foundations of resilience thinking is an important building block for developing more holistic and adaptive approaches to conservation. We conducted a comprehensive review of the history of resilience thinking because resilience thinking provides a working context upon which more effective, synergistic, and systems‐based conservation action can be taken in light of rapid and unpredictable change. Together, resilience science, AM, and EPD bridge the gaps between systems analysis, ecology, and resource management to provide an interdisciplinary approach to solving wicked problems. Fundamentos del Pensamiento sobre Resiliencia     

基于PLS1的哈尔滨市PM2.5与空气污染物相关性分析

以往对PM2.5的研究多集中在气象因子或单一空气污染物对PM2.5质量浓度变化的影响,未考虑多种空气污染物对PM2.5质量浓度的协同作用。通过哈尔滨市环保局发布的2014年1月份（共31 d）市区内主要空气污染物SO2、NO2、PM10、CO、O3、PM2.5的质量浓度数据,运用相关性分析、PLS1和通径分析方法,研究哈尔滨市区内主要空气污染物对PM2.5质量浓度变化的直接影响、通过其他空气污染物的间接影响及污染物之间的协同作用。结果表明,SO2、NO2、PM10、CO 与 PM2.5质量浓度显著性相关,O3与 PM2.5质量浓度相关性不显著,SO2、NO2、PM10、CO 之间存在严重的复相关性。依据相关性分析结果,建立了SO2、NO2、PM10、CO对PM2.5质量浓度的PSL1模型,模型的拟合优度r2为0.852,模型拟合良好。对所建立的模型进行通径分析,结果显示,SO2、NO2、PM10、CO对PM2.5质量浓度变化的直接作用分别为0.005、-0.142、-0.140、1.191,CO对PM2.5质量浓度变化的直接影响作用最大。SO2、NO2、PM10通过CO对PM2.5质量浓度变化的间接作用分别为0.706、1.011、1.118均大于它们对PM2.5质量浓度变化的直接作用。SO2、NO2、PM10、CO对PM2.5质量浓度变化的总决定系数为85.9%。CO是主要空气污染物中影响PM2.5质量浓度变化的主要因素,降低冬季煤炭供暖期CO的排放量,有利于提高空气环境质量,降低对人体的健康危害。     

mCry1Ac基因在抗虫转基因玉米Bt799中的表达特征

采用双抗夹心酶联免疫法(ELISA)定量检测转mCry1 Ac基因抗虫玉米Bt799在不同生育期不同植株部位的mCry1Ac蛋白含量。结果显示:mCry1 Ac基因在整个生育期玉米叶、茎、根和种子中均能表达,mCry1Ac蛋白含量为(0.82±0.10)~(15.83±1.77)μg·g-1;随着生育期和植株部位的不同,mCry1Ac蛋白含量呈现明显的时空动态变化,其中,叶、茎和根中mCry1Ac蛋白含量随转基因玉米生育期的推移均呈增加趋势,并均在完熟期达最高;在除苗期外的其他各生育期叶中mCry1Ac蛋白含量均显著高于其他植株部位,而在完熟期种子中mCry1Ac蛋白含量在各植株部位中最低,为(2.86±1.71)μg·g-1。     

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.     

华北地区夏季大气亚微米颗粒物的半挥发性特征

利用热扩散管TD(Thermal Denuder)与高分辨飞行时间气溶胶质谱仪(HR-ToF-AMS)联用法,于2013年6—7月对华北地区国家环境空气质量评价区域点香河的大气PM₁(亚微米颗粒物)及其组分〔OM(有机质)、SO₄2-、NO₃-、NH₄+、Cl-〕进行连续在线观测,并实现了PM₁不同化学组分半挥发性特征的模拟分析. 结果表明:在观测期间,ρ(PM₁)平均值为 (47.9±47.3) μg/m3,其中OM贡献最大,达到38.2%〔ρ(OM)占ρ(PM₁)的比例,下同〕,之后依次为SO₄2-(33.7%)、NH₄+(13.8%)、NO₃-(12.3%)、Cl-(2.0%). 在PM₁的各化学组分中,NO₃-和Cl-的MFR(质量剩余分数)值最低(约0.40),表明二者的半挥发性最高,当温度为50 ℃时,约60%的NO₃-或Cl-进入气相中;SO₄2-的半挥发性最低,在50 ℃时仍有约90%的质量剩余;而OM和NH₄+的半挥发性居中. NO₃-的半挥发性受大气PM₁污染水平的影响,50 ℃时其半挥发性随着ρ(PM₁)的增加而升高. 当温度从50 ℃升至200 ℃时,残留有机气溶胶的O/C(原子数比)从0.47增至0.60,说明半挥发性组分多为氧化态较低的有机化合物. 此外,真空动力学粒径在60~2 000 nm的颗粒物在不同粒径段表现出相近的半挥发性. 大气PM₁半挥发性的定量分析结果可为全面认识大气颗粒物的物化性质及污染机理提供数据,也有助于空气质量模型的完善.      

希瓦氏菌还原作用下黄钾铁矾的相转变特征及其负载铬的迁移转化规律

黄钾铁矾对酸性矿山废水中铬（Cr）等污染物有较好的固定去除作用.微生物活动对黄钾铁矾的稳定性和Cr的迁移转化特性有重要影响.因此,本研究在厌氧条件下,通过批次实验研究了希瓦氏菌MR-1还原溶解负载Cr黄钾铁矾过程中二次矿物的形成和Cr污染物的迁移转化特性.结果表明,希瓦氏菌能够促进黄钾铁矾的还原溶解.Cr负载能够增强黄钾铁矾的稳定性,抑制矿物的溶解转化.在不含Cr实验组,黄钾铁矾相转变产物为蓝铁矿和针铁矿;而在负载Cr实验组,二次矿物仅为蓝铁矿.在希瓦氏菌还原溶解负载Cr黄钾铁矾的过程中,矿物中有少量的Cr溶出,进入水体,随后又被吸附于新形成的二次矿物中.矿物中的Cr由原来的残渣态转化为不定型铁结合态,固相中Cr释放的风险增大.XPS检测结果表明,矿物表面的Cr（Ⅵ）被还原为Cr（Ⅲ）,Cr的毒性降低.研究结果对进一步理解酸性矿山废水中Fe、S和Cr的地球化学循环过程有重要意义.     

Cloning and expression of RING-finger E3 ubiquitin ligase CsSDIR1 gene in tea plant (Camellia sinensis)北大核心CSCD

Protein ubiquitination regulates many aspects of plant development and stress response. The RING-finger type E3 ubiquitin ligase SDIR1 (salt and drought induced ring finger 1) gene plays a key role in plant stress response. In this study, the full-length cDNA and the promoter sequences of CsSDIR1 were isolated from tea plants using the RT-PCR technology, and its bioinformatics characteristics were systematically analyzed. The expression patterns of CsSDIR1 in various tissues and in response to cold, drought, salt, and ABA treatments were also investigated by quantitative real-time RT-PCR (qRT-PCR). The sequence of CsSDIR1 contains a complete open reading frame of 831 bp, coding for a 276-long amino acid protein with a molecular weight of (Mr) 30.085 × 103 and a theoretical isoelectric point of 6.54. CsSDIR1 was predicted to be a hydrophobic protein localized on the intracellular membranes. The analysis of the amino acid sequence characteristics showed that CsSDIR1 contains two putative transmembrane domains at the N-terminus and a C3H2C3 RING-finger domain at the C-terminus; it shares high similarity with other plants' SDIR1, and has the closest relationship to Actinidia sinensis. A cis-acting regulatory elements prediction showed that the CsSDIR1 promoter contains many cis-acting elements, especially drought and salt stress response elements. The qRT-PCR analysis indicated that the CsSDIR1 gene has a high expression level in stems, followed by roots, leaves, and flowers; the expression of the CsSDIR1 gene is up-regulated by ABA, salt, and drought treatments, whereas it is down-regulated in response to cold stress. These results demonstrated that the CsSDIR1 gene might be involved in the plant stress response of tea trees. © 2018 Science Press. All rights reserved.