整合分析在生态学应用中的优势及存在的问题

整合分析(meta-analysis)是对同一主题下多个独立实验结果进行综合的统计学方法，被认为是到目前为止最好的数量综合方法。结合实例讨论了整合分析在生态学应用中的优势及存在的问题，并介绍了一些解决问题的方法。有明确的选择文献标准、给出了测量指标…效应值、设计严密，分析结果客观性强是其优点；在生态学应用中最严重的问题是选择效应值时面临的生物学意义和统计学特性不能兼顾，其它不足之处主要有选择文献时面临的数据缺失、原文献数据的非正态分布、文章的发表偏见、非随机性选择独立研究等。     

苯并(a)芘对鲫鱼(Carassius auratus)肝脏抗氧化酶的影响

研究了苯并(a)芘(BaP)暴露对鲫鱼肝脏抗氧化酶的影响．共设置4个处理组，浓度分别为每千克体重0．01mg、0．1mg、1mg和10mg，暴露方式采用腹腔注射，分别在暴露后6h、12h、48h和96h测定肝脏超氧化物歧化酶(SOD)、过靴氢酶(CAT)和谷胱甘肽过氧化物酶(GPX)活性．结果显示，所有暴露浓度对SOD活性明显抑制，各处理组活性在暴露后6h均低于对照组，在暴露后12h至48h有所回升，暴露后96h又降至对照水平以下．0．01mg kg^-1、0．1mg kg^-1处理组CA3、活性在暴露期间无显著改变，1mg kg^-1、10mg kg^-1处理组CAT活性在暴露后12h显著升高，暴露后96h回落至对照水平以下，此时10mg kg^-1处理组与对照组差异显著．对照组GPX活性在暴露后出现波动，0．1mg kg^-1处理组在暴露后96h显著低于对照组，而其它处理组活性与对照组在暴露期间无显著差异．结果表明，BaP能对鲫鱼肝脏抗氧化酶产生影响，多种抗氧化酶活性相结合可作为BaP暴露的生物标志物．图3参18     

土壤汞生物可给性的影响因素研究——基于体外模拟(in vitro)法

选取22种典型土壤,应用2种in vitro(模拟体外试验)方法——SBET法(simple bioaccessibility extraction test,生物有效性简化提取法)和PBET法(physiologically-based extraction test,生物原理提取法),定量阐明土壤性质对Hg生物可给性的影响.结果表明,SBET法中Hg的生物可给性为2.91%—35.65%,平均值为13.26%;PBET法中Hg的生物可给性为1.33%—8.69%,平均值为3.93%.所有土壤均表现为SBET法中Hg的生物可给性显著高于PBET法.pH及有机质含量是SBET法和PBET法中决定Hg生物可给性的关键影响因子,分别可以解释67.8%和81.8%的Hg生物可给性的变化;但两种方法中二者的影响程度不同:SBET法中,土壤有机质含量的影响更大,PBET法中,则是pH的影响更大.研究结果表明,污染土壤中Hg的生物可给性可以根据土壤中Hg总量、pH和有机质含量进行预测.     

泸型酒中层酒醅真菌群落的发酵演替规律

考察泸型酒发酵过程中中层酒醅真菌群落的演替规律,探讨菌群演替与环境因子变化的相关性.采用高通量测序技术分析泸型酒中层酒醅真菌群落的演替规律,并运用Mantel test分析不同发酵阶段的真菌群落演替与环境因子变化的相关性.结果表明,中层酒醅发酵过程中存在155个属的真菌,以Kazachstania、Aspergillus、Thermoyces、Thermoascus和Eurotium为主(相对丰度 0.5%).通过聚类分析可将酒醅发酵过程划分为3个阶段:阶段I(0-4 d),阶段II(5-17 d)和阶段III(18-40 d),且3个阶段的酒醅真菌群落结构差异显著(P 0.05). Metastats分析发现,阶段II酒醅真菌群落中Kazachstania的相对丰度比阶段I显著升高(P 0.05),而Trichomonascus、Xeromyces、Thermomyces、Paecilomyces、Aspergillus和Thermoascus相对丰度显著降低(P0.05).与阶段II相比,阶段III酒醅真菌群落中Kazachstania相对丰度显著增长(P 0.05),Thermomyces、Thermoascus、Aspergillus、Wickerhamomyces和Paecilomyces相对丰度显著下降(P 0.05).Mantel test分析发现,阶段I的真菌菌群演替与酒醅水分含量呈显著线性相关(P 0.05),而阶段II和阶段III的真菌菌群演替与酒醅温度、水分、酸度、乙醇浓度变化均没有显著相关性(P 0.05).本研究表明,泸型酒中层酒醅中真菌群落在不同发酵阶段结构差异显著,且酒醅水分变化与发酵前期(0-4 d)真菌群落演替具有显著相关性,结果可为进一步阐明泸型酒发酵过程微生物酿造机理奠定研究基础.     

珍稀濒危植物矮牡丹生存群落优势种种间联结性及群落稳定性

采用方差比率法(VR)、χ~2检验、联结系数(AC)、共同出现百分率(PC)、Pearson相关系数、Spearman秩相关系数以及M.Godron稳定性测定等数量分析方法,对山西稷山矮牡丹(Paeonia suffruticosa Andr. var. spontanea)生存群落中20个优势物种、190个种对间进行种间相关性及群落稳定性分析.结果显示:(1)稷山矮牡丹生存群落20个优势种种群整体表现为不显著负相关性,物种间相对独立,群落稳定性结果(40/60)远离20/80,整体群落不稳定.(2)χ~2检验中不显著关联的对数有168对,占到了88.78%;AC和PC结果都表明20个优势种群落有很大的独立性或随机性,对生境的需求不同,共同出现概率较低;χ~2检验结果、Pearson相关系数半矩阵图、Spearman秩相关系数半矩阵图分别表明检验呈正关联的种对占总对数的38.42%、38.42%、44.74%;检验呈负关联的种对分别占总对数的61.05%、61.05%,54.74%;其中黄刺玫(Rosa xanthina)、连翘(Forsythia suspensa)、辽东栎(Quercus wutaishanica Mayr)与矮牡丹的正相关性相对较显著;黄精(Polygonatum sibiricum)、红柄白鹃梅(Exochorda giraldii)、西北栒子(Cotoneaster zabelii)和黄栌(Cotinus coggygria)与矮牡丹的负相关性相对较显著;(3)根据种群的聚类分析和种间联结测定分析,把矮牡丹生存群落的20个优势种划分为3个生态种组.以上研究表明该群落中种对间的关联性较弱,群落处于不稳定演替阶段,在对矮牡丹保护的同时应加强与其正相关性较强物种在其群落中的保护和建立,促进其群落趋于稳定,以求达到对其实效保护的目的.(图5表6参31)     

海南岛饰纹姬蛙种群的形态变异

揭示海南岛饰纹姬蛙(Microhyla fissipes)种群的形态特征变异及环境在此过程中所发挥的作用,于2016年6月和8月在海南岛共采集到饰纹姬蛙19个种群372只成体标本,测量其7个外部形态性状,并采用聚类分析、主成分分析、Wilcoxon秩和检验和非参数多元方差分析等方法进行比较.结果表明:(1)除儋州种群外,种群头体长大体呈现由西南向东北逐渐增大的趋势;(2)层次聚类及主成分分析结果表明这19个种群可分为2组,即东北组和西南组,而东北组的头体长显著大于西南组,且两组在其他形态量度性状上均差异显著;(3)6月份和8月份采集的群体中,雄性形态差异显著,而雌性形态差异不显著.以上形态差异状况可能是由海南岛独特的南北生态差异所造成,食物资源及捕食压力可能是促进饰纹姬蛙种群朝着更加大型化方向发展的生态因素;本研究结果有助于揭示这一广布物种的形态变异规律及其与生态环境的关系.     

纳米羟基磷灰石对铅镉污染土壤重金属生物可给性的影响研究

通过实验室模拟的方法,分别制备3种污染处理土壤:Pb污染土壤、Cd污染土壤与Pb-Cd复合污染土壤,然后分别向3种污染处理土壤中添加纳米羟基磷灰石,培养180 d,定期采样,并采取两种体外仿生消化方法——PBET法(Physiologically-Based Extraction Test)和USPM法(United States Pharmacopeia Methodology)模拟胃液测定土壤中Pb、Cd的生物可给性,通过对比分析,评价纳米羟基磷灰石对污染土壤重金属生物可给性的影响。研究结果表明,纳米羟基磷灰石显著降低了PBET法对土壤Pb、Cd的提取量,与对照相比,分别下降了44.84%和42.96%。Pb-Cd复合污染明显提高了PBET法对土壤Cd的提取量,但纳米羟基磷灰石处理与复合污染均没有显著影响USPM法对土壤Pb、Cd的提取量。PBET法对土壤Pb、Cd的提取结果与土壤p H值和修复处理呈显著负相关关系;而USPM法对土壤Pb、Cd的提取结果与培养时间呈显著负相关关系。PBET法与USPM法对土壤重金属的提取结果之间不存在显著相关关系,且USPM法对土壤重金属的提取能力显著高于PBET法。USPM法对土壤Pb、Cd的提取量平均分别为PBET法的2.4倍和1.9倍。     

PFOS致大鼠肝毒性及其作用机制研究

通过全氟辛烷磺酸(perfluomoctane sultanate,PFOS)大鼠灌胃染毒实验评价PFOS对肝功能的影响,探讨PFOS肝毒性反应的潜在机制与可能途径。将Sprague Dawley (SD)雄性大鼠随机分为3组,分别以0 mg·kg~(-1)、5 mg·kg~(-1)和10 mg·kg~(-1)PFOS灌胃染毒28 d。以HE和油红染色法观察大鼠肝脏形态改变。ELISA法测定各组谷丙转氨酶(alanine aminotransferase,ALT)、谷草转氨酶(aspartate transaminase,AST)、碱性磷酸酶(alkaline phosphatase,ALP)含量变化。化学比色法测定肝匀浆脂代谢水平和氧化产物含量。RT-PCR法检测肝脏内氧化应激以及脂代谢相关基因表达水平。结果表明,PFOS暴露大鼠体重显著降低而肝脏系数显著增加(P0.05),与对照组相比PFOS组血清肝功能酶均出现随PFOS浓度增加而升高(P0.05)。同时大鼠肝脏谷胱甘肽过氧化物酶(glutathione peroxidase,GSH-px)和丙二醛(malondialdehyde,MDA)水平在高剂量组显著升高(P0.05),超氧化物歧化酶(superoxide dismutase,SOD)含量先显著升高(P0.05)后显著降低(P0.05)。且肝脏中脂代谢水平也随PFOS浓度的增加而出现显著改变(P0.05)。PFOS组基因表达均较对照组显著上升(P0.05)。以上结果说明PFOS具有明显的肝毒性作用,可影响肝脂代谢水平,这可能与PFOS引起的氧化应激所导致的损伤有关。     

全氟辛烷磺酸（PFOS）对小鼠T、B淋巴细胞增殖功能和NK细胞活性的干扰效应研究（Disturbance of Mice Lymphocyte Proliferation Function and NK-cell Activity by Perfluorooctane Sulfonate（PFOS）Exposure）

为初步探讨全氟辛烷磺酸(Perfluorooctane sulfonate,PFOS)的细胞免疫毒性,采用每天1次经口灌胃染毒的方法,研究了PFOS经口重复剂量染毒对C57BL/6小鼠淋巴细胞增殖功能和NK细胞活性的影响.选择雄性C57BL/6小鼠40只,随机分为4组.实验组PFOS染毒剂量分别为5、10、20mg·kg-1(bw),对照组给予2%Tween-80.每天1次经口灌胃染毒7d后,制备脾脏T淋巴细胞悬液,以刀豆蛋白A(ConA)和大肠杆菌脂多糖(LPS)作为刺激源,采用MTT法检测T、B淋巴细胞增殖功能,乳酸脱氢酶释放法检测NK细胞活性.结果表明,10mg·kg-1和20mg·kg-1PFOS染毒组小鼠体重呈明显的下降趋势,且小鼠胸腺和脾脏指数显著低于对照组(p<0.05),而各PFOS染毒组小鼠肝脏指数均显著高于对照组(p<0.05).PFOS各染毒组T淋巴细胞的增殖功能均显著低于对照组(p<0.05);10mg·kg-1和20mg·kg-1PFOS染毒组小鼠NK细胞的活性显著降低(p<0.05).研究结果显示,PFOS暴露可降低小鼠淋巴细胞增殖功能和NK细胞活性,表明PFOS具有免疫抑制效应.     

火箭推进剂单推-Ⅲ对大鼠肺的毒性效应

为探讨新型火箭推进剂单推-Ⅲ(主成分为肼)对大鼠肺的毒性效应及其作用机制,将24只雄性Wistar大鼠随机分为4组:生理盐水对照组、低剂量组、中剂量组和高剂量组,采用气管滴注法染毒,染毒剂量分别为每次0、5.50、13.75、27.50mg·kg-(1以每kg大鼠滴注的肼(mg)计算),每天1次,连续染毒14d,腹主动脉放血处死,检测肺组织病理学改变、氧化损伤、炎性因子和肺组织细胞DNA损伤.结果表明,1)单推-Ⅲ染毒可导致大鼠肺组织炎症:低剂量组表现为轻度肺间质性炎症,中、高剂量组表现为中度肺间质性炎症;2)单推-Ⅲ染毒可导致大鼠肺组织氧化损伤:随着染毒剂量的增加,大鼠支气管肺泡灌洗液中乳酸脱氢酶(LDH)逐渐升高,而总抗氧化能力(T-AOC)逐渐降低,高剂量组与对照组差异显著(p<0.05);3)单推-Ⅲ可导致大鼠肺组织炎性免疫损伤:随着染毒剂量的增加,肺组织匀浆液中肿瘤坏死因子-α(TNF-α)和白细胞介素-6(IL-6)均逐渐升高,高剂量组与对照组差异显著(p<0.05);4)单推-Ⅲ可导致大鼠肺组织细胞DNA损伤:随着染毒剂量的增加,尾部DNA含量、尾长、尾矩、Olive尾矩均逐渐升高,其中高剂量组尾长、Olive尾矩与对照组差异显著(p<0.05).综合以上实验结果可以看出火箭推进剂单推-Ⅲ对大鼠肺组织可产生一定的毒性效应.     

Meta分析及MetaWin软件

综述Meta分析及Metawin软件。Metawin是第一个专为生态学者设计的定量Meta分析软件,它提供了两种假设模型、多种可选择的结合统计量不仅操作简单,而且提出了一种新的非参数检验法──重取样检验。     

A weight-adjusted Peto’s test when cause of death is not assigned

A new statistical testing approach using a weighted logrank statistic is developed for rodent tumorigenicity assays that have a single terminal sacrifice but not cause-of-death data. Instead of using cause-of-death assignment by pathologists, the number of fatal tumors is estimated by a constrained nonparametric maximum likelihood estimation method. For data lacking cause-of-death information, the Peto test is modified with estimated numbers of fatal tumors and a Fleming–Harrington-type weight, which is based on an estimated tumor survival function. A bootstrap resampling method is used to estimate the weight function. The proposed testing method with the weight adjustment appears to improve the performance in various situations of single-sacrifice animal experiments. A Monte Carlo simulation study for the proposed test is conducted to assess size and power of the test. This testing approach is illustrated using a real data set.     

Size-assortative mating and non-reciprocal copulation in a hermaphroditic intertidal limpet: test of the mate availability hypothesis

Mating behaviour and mating patterns are affected to a large extent by body size in both hermaphrodites and gonochorists. Detailed research on mating patterns, mate choice, pre- and post-copulatory sexual selection in marine pulmonates is wanting, thus warranting more attention as a study system in the future. The simultaneous hermaphroditic limpet Siphonaria capensis (Pulmonata: Basommatophora) shows size-dependent fecundity, and acts as a suitable organism to test the effects of body size on mating patterns, mating success, gender expression and reciprocity in hermaphroditic marine gastropods. We mainly used bootstrap resampling techniques to estimate the effects of different factors on mating patterns. In the populations studied, a strong size-assortative mating pattern was observed, where small-scale spatial distribution of potential mating partners (the mate availability hypothesis) could explain 65% of this pattern, while mate choice and mating constraints explaining the rest. No significant difference in mating success between limpets with different body size was found, even though in one population, the sperm recipients were larger than the non-copulating limpets. Interestingly, we found that intromission was non-reciprocal during copulations. This may mean that this species does not conform to the common rule of reciprocity predicted for hermaphrodites, unless there is sex-role alternation between individuals in a mating pair. The mating partners consisted of similar sized, acting males and females, thus without any indication of the body size determining the gender expression. The matings took place in early mornings only at spring tides and the animals were observed laying egg masses only during neap tides. Since siphonariid limpets possess both a spermatheca and a seminal vesicle, which may have either a sperm storing and/or digestive function, post-copulatory sexual selection (e.g., sperm competition) cannot be dismissed.     

Much ado about nothings: using zero similarity points in distance-decay curves

Distance decay is used to describe the (usually exponential) decay in ecological similarity of assemblages between two sites as a function of their distance apart along an environmental gradient. Exponential distance-decay curves are routinely fitted by calculating the ecological similarity between each pair of sites, and fitting a linear regression to the points on a scatter plot of log-similarity vs. distance (x-axis). However, pairs of sites where the assemblages have no species in common pose a problem, because the similarity is zero, and the log transformation cannot be applied. Common fixes to this problem (i.e., either removing or transforming the zero values) are shown to have undesirable consequences and to give widely disparate estimates. A new method is presented as a special case of a generalized dissimilarity model. It is fitted very quickly and easily using existing software, and it does not require removal or transformation of the zero similarity points. Its simplicity makes it convenient for use in conjunction with the resampling methods that are routinely employed to test hypotheses, to obtain standard errors of estimated parameters, or to compare distance-decay curves. A word of caution about standard application of the bootstrap is noted, and modified bootstrap and jackknife alternatives are demonstrated.     

Comparisons between air-transport models via bootstrapped significance tests

The bootstrap resampling method is used to help with the intercomparison of air transport models. Time-by-time analysis of variance and follow up simultaneous comparisons are proposed which do not rely on distributional assumptions for the predictions of the models and which allow errors to be postulated in the observed values of the phenomena under investigation. The techniques are demonstrated using some data from the APSIS experiment.     

A guide to representing variability and uncertainty in biodiversity indicators

Biodiversity indicators are used to inform decisions and measure progress toward global targets, such as the United Nations Sustainable Development Goals. Indicators aggregate and simplify complex information, so underlying information influencing its reliability and interpretation (e.g., variability in data and uncertainty in indicator values) can be lost. Communicating uncertainty is necessary to ensure robust decisions and limit misinterpretations of trends, yet variability and uncertainty are rarely quantified in biodiversity indicators. We developed a guide to representing uncertainty and variability in biodiversity indicators. We considered the key purposes of biodiversity indicators and commonly used methods for representing uncertainty (standard error, bootstrap resampling, and jackknife resampling) and variability (quantiles, standard deviation, median absolute deviation, and mean absolute deviation) with intervals. Using 3 high-profile biodiversity indicators (Red List Index, Living Planet Index, and Ocean Health Index), we tested the use, suitability, and interpretation of each interval method based on the formulation and data types underpinning the indicators. The methods revealed vastly different information; indicator formula and data distribution affected the suitability of each interval method. Because the data underpinning each indicator were not normally distributed, methods relying on normality or symmetrical spread were unsuitable. Quantiles, bootstrapping, and jackknifing provided useful information about the underlying variability and uncertainty. We built a decision tree to inform selection of the appropriate interval method to represent uncertainty or variation in biodiversity indicators, depending on data type and objectives. Our guide supports transparent and effective communication of biodiversity indicator trends to facilitate accurate interpretation by decision makers.     

Distribution-free two-sample comparisons in the case of heterogeneous variances

Behavioral ecologists are often faced with a situation where they need to compare the central tendencies of two samples. The standard tools of the t test and Mann–Whitney U test (equivalent to the Wilcoxon rank-sum test) are unreliable when the variances of the groups are different. The problem is particularly severe when sample sizes are different between groups. The unequal-variance t test (Welch test) may not be suitable for nonnormal data. Here, we propose the use of Brunner and Munzel’s generalized Wilcoxon test followed by randomization to allow for small sample sizes. This tests whether the probability of an individual from one population being bigger than an individual from the other deviates from random expectation. This probability may sometimes be a more clear and informative measure of difference between the groups than a difference in more commonly used measures of central tendency (such as the mean). We provide a recipe for carrying out a statistical test of the null hypothesis that this probability is 50% and demonstrate the effectiveness of this technique for sample sizes typical in behavioral ecology. Although the test is not available in any commercial software package, it is relatively straightforward to implement for anyone with some programming ability. Furthermore, implementations in R and SAS are freely available on the internet.     

Resampling from stochastic simulations

To model the uncertainty of an estimate of a global property, the estimation process is repeated on multiple simulated fields, with the same sampling strategy and estimation algorithm. As opposed to conventional bootstrap, this resampling scheme allows for spatially correlated data and the common situation of preferential and biased sampling. The practice of this technique is developed on a large data set where the reference sampling distributions are available. Comparison of the resampled distributions to that reference shows the probability intervals obtained by resampling to be reasonably accurate and conservative, provided the original and actual sample has been corrected for the major biases induced by preferential sampling.Andre G. Journel is a Professor of Petroleum Engineering at Stanford University with a joint appointment in the Department of Geological and Environmental Sciences. He is, also, Director of the Stanford Center for Reservoir Forecasting. Professor Journel has pioneered applications of geostatistical techniques in the mining/petroleum industry and extended his expertise to environmental applications and repository site characterization. Most notably, he developed the concept of non-parametric geostatistics and stochastic imaging with application to modeling uncertainty in reservoir/site characterization. Although the research described in this article has been supported by the United States Environmental Protection Agency under Cooperative Agreement CR819407, it has not been subjected to Agency review and therefore does not necessarily reflect the views of the Agency and no official endorsement should be inferred.     

Quality of basic data and method to identify shape affect richness-altitude relationships in meta-analysis

We compiled 109 species richness-altitude (SRA) relationships in arthropods to test the hypothesis that identification of shape and robustness of pattern are contingent on the selection of studies included in meta-analysis. We used attributes of their sampling design to distinguish three subsets of data according to stringent, intermediate, and lax selection criteria. We tested (1) whether uncertainty over identification of shape increases as the criteria of inclusion of studies relaxes and (2) whether studies that conform to stringent selection criteria show robustness in SRA patterns to variation in method used to identify shape. We identified the shape of each SRA relationship using statistical and visual methods; data sets that suggested several shapes as equally likely were sorted out by consensus. Arthropods suggested multiple forms in the SRA relationship, with predominance of hump-shaped patterns in the stringent subset. Uncertainty over identification of shape increased after application of intermediate and lax selection criteria. The method of analysis interacted with the quality of basic data to influence the relative distribution of patterns. We concluded that the gathering of large quantities of data is insufficient and that critical evaluation of literature is crucial to infer with confidence the general shape of ecological patterns in meta-analysis.     

In search of quorum effects in metacommunity structure: species co-occurrence analyses

Alternative models of community assembly emphasize regional, stochastic, dispersal-based processes or local, deterministic, niche-based processes. Community ecology's historical focus on local processes implicitly assumes that local processes surpass regional processes over time or across space to derive nonrandom metacommunity structure (i.e., a quorum effect). Quorum effects are expected late in succession among nearby sites, whereas quorum effects are not expected early in succession among distant sites. I conducted a meta-analysis of zooplankton data sets encompassing time scales of one to thousands of years and spatial scales of <1 m to thousands of kilometers. Species co-occurrence analyses statistically evaluated presence/absence patterns relative to random patterns obtained with Monte Carlo null models. A series of weighted analyses was conducted and alternative randomization algorithms and null models were evaluated. Most zooplankton metacommunities were randomly structured in unweighted analyses, and the distribution of significant structure did not follow quorum effect predictions. Weighted analyses (e.g., by habitat area) revealed significant, nonrandom structure in most zooplankton metacommunities, but the distribution of significant structure still did not adhere well to quorum effect predictions. Finally, additional weighting for study scale (number of sites) nullified most significant area-weighted structure, and again, the distribution of significant structure did not follow quorum effect predictions. Overall, a quorum effect was not supported, perhaps related to zooplankton life histories and energetics and/or the quorum effect itself. Results at the presence/absence level of resolution indicated that local processes did not generally override regional processes over time or across space to drive community structure. A full integration of dispersal- and niche-based concepts in metacommunity dynamics will be most fruitful for unraveling community assembly. Species co-occurrence analyses were scale dependent (habitat area and study size). Future analyses should use weights for important factors (e.g., habitat area), and meta-analyses should include study scale as an additional factor contributing to apparent patterns.