长江口及邻近海域富营养化指标响应变量参照状态的确定

对长江口富营养化指标中的响应变量进行了筛选,并在长江口分区的基础上,运用参照点或观测点指标频数分布曲线法,对1992年-2010年的数据进行分析,确定了长江口外海区和舟山海区富营养化指标中响应变量的参照状态.选择叶绿素a和底层溶解氧作为响应指标的必选指标,浮游植物密度和CODMn作为辅助指标.经分析,长江口口外海区叶绿素a、浮游植物密度、CODMn和底层溶解氧的春夏秋3个季节的参照状态分别为0.87mg,/m3,17.44× 103个/L,0.42mg/L,8.36mg/L;1.88mg/m3,25.96×103个/L,0.56mg/L,4.22mg/L;0.84mg/m3,12.10×103个/L,0.46mg/L,6.95mg/L;舟山海区叶绿素a、浮游植物密度、CODMn和溶解氧的春夏秋3个季节的参照状态分别为0.73mg/m3,6.77×103个/L,0.51 mg/L,8.75mg/L;1.00mg/m3,9.72×103个/L,0.37mg/L,5.94mg/L;0.78mg/m3,4.59×103个/L,0.55mg/L,7.40mg/L.本研究确定的参照状态值能较为客观的反映该海域的富营养化参照状态,且不同分区,不同季节间的指标的参照状态亦存在着显著的差异.     

新疆奇台荒漠植物群落的数量分类及土壤环境解释

为阐明古尔班通古特沙漠南缘荒漠植物群落的分类及与土壤因子的相关关系, 作者于2005年6–7月在新疆奇台县采用机械布设样线和样线上随机布设样地的方法进行了野外调查。共设置48块20 m×10 m的样方, 每个样方中又梅花状设置5个1 m×1 m的草本样方进行植被调查。植被调查结束后, 选择群落外貌上差异显著的样地进行土壤取样(取土深度分别为0 cm、10 cm、30 cm、50 cm、80 cm), 共获得20个样方的土壤样本。以植物重要值作为衡量植物组成相似性的指标, 应用逐步聚类的方法将调查区域植被划分为4种类型: 芦苇(Phragmites australis)+芨芨草(Achnatherum splendens)群落, 梭梭(Haloxylon ammodendron)–枇杷柴(Reaumuria songarica)+西伯利亚白刺群落(Nitraria sibirica), 梭梭–心叶驼绒藜(Ceratoides ewersmanniana)–白茎绢蒿(Seriphidium terrae-albae)群落和心叶驼绒藜–骆驼刺(Alhagi sparsifolia)群落。不同群落类型土壤因子的主成分分析的结果表明: 提取3个主分量能够解释85.65％的群落间土壤因子差异, 第1主分量与土壤平均pH值和深层土壤pH值相关, 第2主分量与平均有机质含量和土壤浅层有机质含量相关, 而第3主分量与平均土壤含盐量和土壤浅层含盐量相关。     

Fatty acid composition of Simonsiella strains

Gas-liquid chromatography of methyl esters of bound fatty acids extracted from the cells of 48 Simonsiella strains showed that these aerobic, gliding, multicellular-filamentous bacteria have fatty acid profiles of the pattern considered typical of Gramnegative eubacteria. All strains contained predominantly tetradecanoic acid (29.5%), 9-hexadecenoic acid (22.2%), an unidentified acid with an equivalent chain length of approximately 20 carbon atoms (15.8%), and dodecanoic acid (11.4%).Discriminant analysis of the mean relative percentages of 12 fatty acids correctly assigned 94% of the strains to groups based on their source of origin (i.e., the oral cavities of sheep, cat, human or dog); the relative amounts of only 3 of the fatty acids (9-octadecenoic acid, hexadecanoic acid, and tetradecanoic acid) provided most of this discrimination.     

影响天然林下层植物物种多样性的林分因子的研究

以我国东北过伐林区3种典型森林类型为对象,用多元逐步回归方法来研究影响天然林下层植物多样性的林分因子,尤其是与森林经营有关的林分因子,从而通过经营来维持和增加物种多样性。研究表明,与经营有关的因子中对下层植物多样性有显著影响的有林分郁闭度、公顷株数和树种多样性。因此,在林分发展的一定阶段,应采取合理经营措施如采伐来控制林分密度,保持多树种的混交,来维持和增加树种多样性。     

Factors influencing the spatial distribution of forest plant species in hedgerows of North-western Germany

In North-western Germany woodland fragmentation has caused a decline in many forest plant species. Hedgerows partly offer a similar environment as forests and have been identified as potential habitats for forest plants in various studies from North America and Western Europe. The objective of this study was to examine whether this applies also to Central Europe and which variables affect the spatial distribution and abundance of forest plant species in hedgerows on a local scale. Three hedgerow networks north of the city of Bremen, Germany, were selected as study areas and divided into totally 515 hedgerow segments. In each segment we recorded all vascular plants and a large number of explanatory variables relating to structure, spatial configuration, environment and management. Averaged across species there was a predominant effect of environmental factors on the occurrence of forest species in the hedgerows, followed by spatial configuration and management. Hedgerow structure was found to be less important. In general, forest species were favored by low nutrient and light availability as well as high connectivity with other hedgerows or forest; they avoided hedgerows with a west-easterly orientation and an adjacent land use in the form of fields or grasslands. Forest species found and not found in hedgerows did not differ in their environmental preferences or life history traits. The number of threatened forest species in the hedgerows, however, was lower than expected with respect to their overall proportion to the total number of forest species in the region.     

基于MaxEnt模型的甘肃安西极旱荒漠国家级自然保护区北山羊生境评估

明晰甘肃安西极旱荒漠国家级自然保护区珍稀濒危物种北山羊的分布格局,并阐释气候变化和人类活动对北山羊的影响,对今后北山羊生境管理和物种保护具有重要意义。基于北山羊实测分布点记录和环境变量数据,结合MaxEnt模型和ArcGIS空间分析功能,利用CMIP6的8个气候模式均值预测中度发展路径（SSP2-4.5）下,基准期（1970-2000年）和未来气候（2041-2060年、2081-2100年）变化情景下,甘肃安西极旱荒漠国家级自然保护区北山羊的潜在适生区分布范围及变化,并综合贡献率和置换重要性值对北山羊生境选择关键环境因子进行了分析。研究结果表明：（1） MaxEnt模型的预测精度较高,三种气候条件下ROC曲线下面积（AUC,Area Under Curve）>0.97,且真实技巧统计（TSS,True Skill Statistic）>0.90,模拟结果可靠。（2）影响北山羊生境选择的主要环境因子为气候条件（降水量季节性变异系数和等温性）、海拔和人为干扰（距泉和居名点距离）。水是保护区北山羊生存的最基本要素,气候条件共同控制北山羊生境条件。此外,北山羊习性决定其生境宜选择高海拔和远离人类活动影响地区。（3）基准期保护区北山羊主要分布在北片和南片高海拔山区,面积365.77 km²（占整个保护区的4.31%）,北山羊适生区面积北片>南片、中高等适生区主要位于保护区北片。（4） CMIP6未来气候变化情景下,随着保护区生态环境改善和濒危物种保护措施的实施,北山羊潜在适生区面积呈增加趋势,但是受北山羊近亲繁殖的影响,整体上北山羊数量和适生区面积增加并不显著且有向南部及高海拔地区转移趋势。     

引种捕食螨胡瓜新小绥螨在中国的适生区分布预测

胡瓜新小绥螨(Neoseiulus cucumeris)是一种商业化的广食性生防天敌,可以防治多种农业害螨和害虫,具有重要的经济和生态价值。但是作为一种外来引种的捕食螨,它在我国的适生区域分布以及气候变化对其分布的影响尚不明确。根据胡瓜新小绥螨的现有分布点和19个生物气候因子,利用刀切法评估关键气候因素的重要性,并采用Maxent生态位模型分别预测了目前和未来气候条件下它在中国分布情况,分析了其在中国的潜在适生区域的变化。结果表明模型预测得到的受试者工作特征曲线ROC曲线下的面积AUC(Area under curve)值为0.87,表明模型的准确度好。最冷季节的降水量(Bio_19)、等温性(Bio_3)和气温季节性(Bio_4)是影响胡瓜新小绥螨适生性的最重要的环境因子, 对模型的贡献率分别为36.2%、25% 和18.1%。目前胡瓜新小绥螨的适生区面积约占我国陆地面积的60%,在未来气候条件下,其适生区域有进一步扩大的趋势,在2050年其中高度适生区域扩张至63%。不同时期胡瓜新小绥螨的分布中心比较稳定,均分布于四川省内,但有向东北迁移的趋势。本研究明确了胡瓜新小绥螨在中国适宜的释放区域及可能定殖的区域,为该引种天敌的合理利用提供了理论依据。     

1999‒2015年红塔区伤寒与副伤寒流行特征和气象变量的研究

目的 分析1999‒2015年红塔区伤寒与副伤寒（typhoid and paratyphoid fever,TPF）地方病区域流行特征和气象变量的关系,为TPF监测控制和危险因素评价提供科学依据。方法 采用描述流行病学方法和自主研发计算机软件建立中国疾病预防控制信息系统红塔区TPF病例分布与流行特征数据库,用Pearson相关分析和多元线性逐步回归分析研究TPF发病和气象变量关系。结果 1999‒2015年报告TPF病例数为8 398例,1999、2015年分别报告23、44例。1999‒2015年期间每年3~5月、6~10月、11月~次年2月分别为发病上升期（月均增长率63.8%）、高峰期（月均降低率2.0%）和下降期（月均降低率25.7%）,每年度病例数都呈现3月~10月季节性升高和11月~次年2月季节性降低;2000年8月至2010年12月每月病例数都大于8例,2000‒2002、2004‒2005、2005‒2007、2007‒2008、2008‒2010年出现五个高强度流行峰,峰期范围是12～24个月,周期范围是11～40个月;2001、2004、2006、2007、2009年五个高峰年度6~10月病例数范围分别为86～217、67～215、125～216、97～131、63～95例;1999、2000、2002、2003、2005、2008、2010、2015年八个低峰年度6月~10月病例数范围分别为1～3、1～17、32～60、30～43、46～55、43～78、22～61、2～11例。单因素分析TPF月平均发病率与月平均降雨量（r=0.825,P<0.01）、月平均气温（r=0.797,P<0.01）和月平均相对湿度（r=0.706,P<0.05）呈正相关;经多元逐步回归分析建立TPF月平均发病率（Y）与月平均降雨量（X）的拟合模型方程Y=4.563+0.051X。结论 红塔区TPF发病呈现季节性升高与降低、周期性流行、长期趋势特点;发病率与降雨量、气温、相对湿度呈正相关;传染源积累、重污染源形成、暴露人群增加驱动着流行特征与气象变量关系;相应规律、机制、政策、评估有助TPF的监测控制。     

Hypothesis tests for stratified mark‐specific proportional hazards models with missing covariates,with application to HIV vaccine efficacy trials

This article develops hypothesis testing procedures for the stratified mark‐specific proportional hazards model with missing covariates where the baseline functions may vary with strata. The mark‐specific proportional hazards model has been studied to evaluate mark‐specific relative risks where the mark is the genetic distance of an infecting HIV sequence to an HIV sequence represented inside the vaccine. This research is motivated by analyzing the RV144 phase 3 HIV vaccine efficacy trial, to understand associations of immune response biomarkers on the mark‐specific hazard of HIV infection, where the biomarkers are sampled via a two‐phase sampling nested case‐control design. We test whether the mark‐specific relative risks are unity and how they change with the mark. The developed procedures enable assessment of whether risk of HIV infection with HIV variants close or far from the vaccine sequence are modified by immune responses induced by the HIV vaccine; this question is interesting because vaccine protection occurs through immune responses directed at specific HIV sequences. The test statistics are constructed based on augmented inverse probability weighted complete‐case estimators. The asymptotic properties and finite‐sample performances of the testing procedures are investigated, demonstrating double‐robustness and effectiveness of the predictive auxiliaries to recover efficiency. The finite‐sample performance of the proposed tests are examined through a comprehensive simulation study. The methods are applied to the RV144 trial.     

Forest cover dynamics analysis and prediction modeling using logistic regression model

Forest cover conversion and depletion are of global concern due to their role in global warming. The present study attempted to study the forest cover dynamics and prediction modeling in Bhanupratappur Forest Division of Kanker district in Chhattisgarh province of India. The study aims to examine and analyze the various explanatory variables associated with forest conversion process and predict forest cover change using logistic regression model (LRM). The forest cover for the periods 1990 and 2000, derived from Landsat TM satellite imagery, was used to predict the forest cover for 2010. The predictive performance of the model was assessed by comparing the model-predicted forest cover with the actual forest cover for 2010. To explain the effects of anthropogenic pressure on forest, this study considered three distance variables viz., distance from forest edge, roads and settlements, and slope position classes as explanatory variables of forest change. The highest regression coefficient (β = −26.892) was noticed in case of distance from forest edge, which signifies the higher probability of forest change in areas that are closer to the forest edges. The analysis showed that forest cover has undergone continuous change between 1990 and 2010, leading to the loss of 107.2 km² of forest area. The LRM successfully predicted the forest cover for the period 2010 with reasonably high accuracy (ROC = 87%).