Importance of timely metadata curation to the global surveillance of genetic diversity

Genetic diversity within species represents a fundamental yet underappreciated level of biodiversity. Because genetic diversity can indicate species resilience to changing climate, its measurement is relevant to many national and global conservation policy targets. Many studies produce large amounts of genome-scale genetic diversity data for wild populations, but most (87%) do not include the associated spatial and temporal metadata necessary for them to be reused in monitoring programs or for acknowledging the sovereignty of nations or Indigenous peoples. We undertook a distributed datathon to quantify the availability of these missing metadata and to test the hypothesis that their availability decays with time. We also worked to remediate missing metadata by extracting them from associated published papers, online repositories, and direct communication with authors. Starting with 848 candidate genomic data sets (reduced representation and whole genome) from the International Nucleotide Sequence Database Collaboration, we determined that 561 contained mostly samples from wild populations. We successfully restored spatiotemporal metadata for 78% of these 561 data sets (n = 440 data sets with data on 45,105 individuals from 762 species in 17 phyla). Examining papers and online repositories was much more fruitful than contacting 351 authors, who replied to our email requests 45% of the time. Overall, 23% of our email queries to authors unearthed useful metadata. The probability of retrieving spatiotemporal metadata declined significantly as age of the data set increased. There was a 13.5% yearly decrease in metadata associated with published papers or online repositories and up to a 22% yearly decrease in metadata that were only available from authors. This rapid decay in metadata availability, mirrored in studies of other types of biological data, should motivate swift updates to data-sharing policies and researcher practices to ensure that the valuable context provided by metadata is not lost to conservation science forever.     

基于Multi-class SVM的车辆换道行为识别模型研究

自动安全换道是车辆实现无人驾驶的关键,为精确识别行驶车辆换道状态,保证行车安全,设计了一种基于多分类支持向量机(Multi-class Support Vector Machine,Multiclass SVM)的车辆换道识别模型。从NGSIM数据集中选取美国101公路车辆轨迹数据进行分类处理,并将车辆换道过程划分为车辆跟驰阶段、车辆换道准备阶段和车辆换道执行阶段。采用网格搜索结合粒子群优化算法(Grid Search-PSO)对SVM模型中惩罚参数C和核参数g进行寻优标定,利用多分类支持向量机换道识别模型对样本数据进行训练和测试,模型测试精度达97.68%。研究表明,模型能够很好地识别车辆在换道过程中的行为状态,为车辆换道阶段的研究提供支持。     

俄罗斯布里亚特共和国植被NPP对气候变化的时空响应

以遥感和气象数据为主要数据源,运用改进后的CASA模型,估算了俄罗斯布里亚特共和国2000-2008年的植被NPP,并验证了模型的精度,分析了该地区植被NPP的时空变化规律及其与气候因子的相互关系。研究结果表明:时间上,植被NPP年际上呈现为在波动中上升,月份上表现为先升后降的趋势;空间上,植被NPP随经度的增加而增大,随纬度的增加而减小,由西南到东北逐渐递增的趋势;不同植被类型的NPP也不同,从大到小依此为:草地与沼泽林>森林>森林与草原>稀树草原>高山植被。其变化主要受气温和降水量变化的作用。改进后的CASA模型运用于布里亚特共和国植被NPP估算的精度较高。该研究对中国北方植被NPP估算和生态跨境研究具有借鉴意义。     

Modeling net primary production of a fast-growing forest using a light use efficiency model

As interest grows in the quantification of global carbon cycles, Light Use Efficiency (LUE) model predictions of the forest net primary production (NPP) are being developed at an accelerating rate. Such models can provide useful predictions at large scales, but evaluating their performance has been difficult. In this study, a remote sensing-based LUE model was established to estimate forest NPP. Using the forest inventory data (FID) from the regional forest inventory survey in China and established allometric biomass equations, we calculated the biomass, the biomass increment, and the NPP of Eucalyptus urophylla (E. urophylla) plantation plots in the forestry jurisdiction of the Leizhou Forestry Bureau, Southern China. The FID-based NPP and the NPP from LUE model predictions were then compared to each other. Results show that the NPP from model predictions at a spatial resolution of 30 m × 30 m varied from 0 to 265 gC/(m² month) and showed regional differences. In addition, the stand age had variable effects on the average individual biomass of the E. urophylla plantation plots. The average individual biomass of the young and mid-age forests increased exponentially and logarithmically with the stand age (R² = 0.9178 and R² = 0.8683), respectively. For young and mid-age E. urophylla plantation plots, the LUE model-predicted NPP was fairly consistent with the FID-based NPP, but the model predictions of the NPP were higher than the estimates from FID. Through the analysis of the causes of uncertainty and the possible reasons for the discrepancy between the model-based NPP and FID-based NPP, the FID-derived estimates provided a foundation for model evaluation.     

Identifying Anomalous Reports of Putatively Extinct Species and Why It Matters

Abstract:  As species become very rare and approach extinction, purported sightings can stir controversy, especially when scarce management resources are at stake. We used quantitative methods to identify reports that do not fit prior sighting patterns. We also examined the effects of including records that meet different evidentiary standards on quantitative extinction assessments for four charismatic bird species that might be extinct: Eskimo Curlew ( Numenius borealis ), Ivory-billed Woodpecker ( Campephilus principalis ), Nukupu`u ( Hemignathus lucidus ), and O`ahu `Alauahio ( Paroreomyza maculata ). For all four species the probability of there being a valid sighting today, given the past pattern of verified sightings, was estimated to be very low. The estimates of extinction dates and the chance of new sightings, however, differed considerably depending on the criteria used for data inclusion. When a historical sighting record lacked long periods without sightings, the likelihood of new sightings declined quickly with time since the last confirmed sighting. For species with this type of historical record, therefore, new reports should meet an especially high burden of proof to be acceptable. Such quantitative models could be incorporated into the International Union for Conservation of Nature's Red List criteria to set evidentiary standards required for unconfirmed sightings of "possibly extinct" species and to standardize extinction assessments across species.     

生态毒理数据筛查与评价准则研究

化学品生态风险评价和水质基准研究需要大量生态毒理数据,由于目前关于化学品毒性效应的研究较多,不同文献对同一测试终点的报道常常存在一定的差异,数据选择不当会直接影响最终评价结果。为了降低专业人员在数据筛选过程中的主观影响,有必要制定一套科学合理、操作性强的数据筛查与评价准则。本文整理比较了美国、荷兰、德国和澳大利亚等4个国家的5个毒理数据筛查与评价方法,并以荷兰的CRED方法为主,结合另外4个筛选方法以及现有的水质基准推导指南和生态风险评价技术导则,从可靠性、相关性、精确性三个方面详细阐述了数据质量评价标准与使用规范。其中数据质量评价包括五个方面:(1)实验设计,包括测试标准、操作规程、数据有效性、对照组设置;(2)实验试剂的纯度及其杂质的物理化学性质;(3)受试生物的基本信息和来源;(4)暴露条件,包括试验系统、暴露浓度设置及变化、暴露时间、生物负荷;(5)数据分析,包括平行样、统计分析方法、浓度-效应关系、原始数据;数据使用规范主要考虑受试生物、测试终点和暴露场景与评价目标的相关性,以及生态风险评价和水质基准推导对数据精确性的要求。这些均可为我国从事生态风险评价和水质基准研究的工作人员提供有益借鉴,使数据筛选过程更加客观、统一,同时还可以作为毒理实验论文撰写依据,提高数据报道质量。     

东北野生五味子种群特征及其与环境因子的关系

五味子(Schisandra chinensis)是著名的传统中药材,主要分布在我国东北地区. 受过度采摘和毁林开荒等不科学利用方式的影响,野生五味子资源急剧恶化. 沿长白山山脉和小兴安岭山脉调查了17个野生五味子种群,分析了种群特征、环境因子特征及二者的相关关系. 结果表明:①五味子果实质量与纬度呈极显著负相关,基径与海拔呈显著正相关,而种群密度空间分布规律不明显;五味子果实质量、基径和种群密度间不存在显著相关性. ②五味子果实千粒质量和基径平均值分别为(69.05±12.80) g和(0.61±0.13)cm,种群密度大,约50%五味子种群密度达到4级(>1.5～2.0株/m2). ③五味子野生种群采样点的土壤pH(5.34～6.98)呈酸性;w(SOC)(SOC为土壤有机碳)在4.42%～18.47%之间,差异较大;w(TN)、w(TK)和w(TP)平均值分别为0.72%±0.28%、1.74%±0.31%和0.10%±0.03%. ④年降水量在474~928mm之间;年日照时长变化幅度小,在2219.3～2703.7h之间;年均气温和年均相对湿度的平均值分别为(3.46±1.44) ℃和68.9%±2.7%. 主成分分析表明,五味子果实质量受环境因子影响显著,其中年均气温的影响最大,其次是w(TP)、w(TN)、w(SOC)和年降水量;而基径和种群密度受环境因子的影响不显著. 对野生五味子种群生长限制因子的分析结果可为该种群保护、人工栽培与调控奠定理论基础.      

降雨资料时间序列长度对降雨侵蚀力平均值置信度的影响

降雨资料时间序列长度是计算多年平均降雨侵蚀力过程中的重要不确定性因素.论文以中国601个气象站1980-2009年逐月降雨资料为数据源,利用Wischmeier经验公式计算了各气象站逐年降雨侵蚀力(R因子),用简单随机抽样方法抽取样本容量分别为30 a、 20 a、 10 a和5 a 四种不同的R值样本,计算了R平均值相对允许误差10%和25%条件下抽样估计的置信度.结果表明:降雨资料的时间序列长度对R平均值的估计置信度有显著影响;R平均值置信度存在明显的地域差异,长江以南、 青藏高原东部以及河西走廊南部的祁连山地区置信度较高;在降雨资料有限的情况下,必须根据土壤侵蚀研究的精度要求分析R平均值的抽样误差及其置信度,以保证土壤侵蚀定量预报的客观性与准确性.     

A fate constant data program

A program for compiling equilibrium and kinetic constants for predicting chemical transport and transformation in the environment is described. The fate constant data are obtained by searching the literature for reported measurements, by convening a panel of experts to postulate transformation pathways and products, by using computational techniques to estimate values, and by performing laboratory studies when measurements cannot be found or computed. Emphasis is placed throughout the program on quality control features to assure the reliability of the data.