水生态基准方法学概述及建立我国水生态基准的探讨（Methodologies for Deriving Water Quality Criteria to Protect Aquatic Life（ALC）and Proposal for Development of ALC in China: A Review）

水生态基准的研究和制定对于控制进入水环境污染物的种类和数量,保护水体生物多样性及整个水生态系统的结构和功能具有重要意义.论文对不同国家和地区现有的主要水生态基准推导方法进行了概述,并从基准保护目标、数据的收集与评估、基准的计算方法等几个方面对各国水质基准推导方法进行了比较.参照国外水质基准的推导过程及我国水生态系统的特征,探讨了合理可行的水生态基准保护目标、计算方法及推导流程,并对我国水生态基准的推导中可能存在的问题进行了讨论.     

我国六价铬淡水水生生物安全基准推导研究

参照美国国家环境保护局(USEPA)"推导保护水生生物及其用途的国家水质基准的技术指南"的程序和规范,筛选了我国广泛存在的淡水水生生物物种,收集现有的急性和慢性毒性数据,结合课题组实验得到的部分本土生物毒性数据,分别采用物种敏感度排序法(SSR)、物种敏感度分布法(SSD)以及澳大利亚的水质基准技术方法对我国六价铬的淡水水生生物安全基准进行了推导。获得了我国淡水水生生物的六价铬的双值基准,3种方法得到的基准最大浓度(CMC)分别为23.97、22.84、29.06μg·L-1,基准连续浓度(CCC)分别为14.63、10.35、9.00μg·L-1,在同一个数量级上,但与美国的基准值有一些差异,建议使用SSD法推导CMC值和CCC值。研究结果可为我国水质基准的制定提供一些有用的基础资料。     

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。     

我国铜的淡水生物水质基准研究

铜是生命体必需的一种微量元素,当铜的浓度超过一定范围时,又会对机体产生一定的毒害作用.为了有效控制铜给水生生物带来的不利影响,亟需开展铜的水质基准研究工作.以我国淡水生态系统为保护对象,收集和筛选了淡水水体中的生物物种和相应的毒性数据.用评价因子法、毒性百分数排序法和物种敏感度分布法分别推导了我国铜的淡水生物水质基准....     

淡水水生态基准方法学研究:繁殖/生殖毒性类化合物水生态基准探讨

繁殖/生殖毒性类化合物由于特殊的毒理作用模式(mode of action,MOA),通过影响生物繁衍影响到种群和群落,因此依靠基于急、慢性毒性测试终点和传统基准推导方法推导的水生态基准值并不能够为水生生物群落结构提供足够的保护。本文根据文献资料,分析了推导此类化合物水生态基准时的关键科学问题,包括繁殖/生殖毒性类化合物MOA,毒性数据类型,受试物种选择,以及不同生命阶段、多代毒性测试和测试终点的判别和选择。并用所收集的壬基酚数据,尝试推导了基于水生生物生殖毒性的水生态基准值。研究得出基于生殖毒性的壬基酚预测无观察效应浓度(PNEC)值为0.12μg·L-1,其数值比美国环境保护局根据传统基准方法推导的基准持续浓度(CCC)的6.59μg·L-1低了近50倍。因此,基于其繁殖毒性(包括产卵量、受精率、孵化率、多代效应以及种群变化等)的实验结果更适合用于具有繁殖/生殖毒性污染物水生态基准的推导。     

我国硝基苯的海水水质基准及生态风险评估研究

以一种重要的化工原料硝基苯为研究对象,通过收集、筛选我国本土物种的硝基苯海水生物毒性数据,同时针对我国海区生物特点补充8种典型海洋受试生物的毒理学实验,应用物种敏感度分布(SSD)方法推导了用于保护水生生物的我国硝基苯海水水质基准值。在此基础上,尝试应用2种概率生态风险评估方法初步评估了硝基苯在我国东海椒江口水体中的生态风险。研究结果表明,用于保护我国海水生物的硝基苯水质基准高值为1.42 mg·L-1,低值为0.037 mg·L-1,与应用SSD方法推导的硝基苯淡水水质基准差异不大。商值概率分布法和联合概率曲线法的风险表征结果表明,硝基苯对椒江口中的水生生物存在潜在的生态风险,需要管理部门采取一定的风险管控措施。研究结果有望为我国水质基准、生态风险研究及硝基苯的海水水质标准制定提供参考。     

水生态模拟系统及其在化学品生态风险评估中的应用

水生态模拟系统是用于高层次化学品生态风险评估的测试模型,目前在国外已经广泛用于工业化学品、农药、兽药、重金属等单一化学物质和复杂混合物的生态风险评估研究,而我国的相关研究比较匮乏。随着我国化学品风险评估体系的完善,水生态模拟系统测试必将作为作为单一生物毒性测试的有效补充。在此背景下,简述了水生态模拟系统的分类、研究方法和结果外推方法;从单一化学物质暴露作用下的生态危害评估、多种化学物质联合暴露作用下的生态危害评估以及目标化学物质的归趋分析三个方面阐述了水生态模拟系统在国内外化学品风险评估科学研究中的应用,对比了水生态模拟系统和单一物种毒性测试结果和基于两种测试数据的生态危害评估结果。与此同时,分析了水生态模拟系统在国内外化学品环境管理中的应用情况。在此基础上,对我国发展水生态模拟系统所存在的问题及解决方案提出了建议。     

红霉素水生生物基准推导和对中国部分水体生态风险初步评估

红霉素是大环内酯类抗生素,环境中红霉素残留具有较高的生态风险和健康风险,而中国目前尚缺乏红霉素的淡水水生生物基准值,因而研究适合中国流域水环境的红霉素水生生物基准,对于保护中国淡水水生生物以及水质基准的研究具有重要意义。该研究搜集筛选了红霉素对中国淡水生物的急慢性毒性数据,共获得3门8科的10个急性毒性数据和2门4科的4个慢性毒性数据。利用美国环境保护局推荐的物种敏感度排序法(SSR)推导红霉素的水生生物基准,同时以log-normal SSD法和log-logisticSSD法对基准计算结果进行了比对。比较了3种方法的优缺点,以及与国内外已有研究基准值之间的差异及形成原因,分析了影响红霉素水生生物基准的关键因素。得出采用SSR法推导的保护中国水生生物的红霉素急性基准值(CMC)为0.47μg·L~(-1),慢性基准值(CCC)为0.10μg·L~(-1)相对可行。将该研究推导出的红霉素慢性基准值(CCC)与中国部分江河和湖泊中红霉素暴露浓度相比较,采用风险商值(RQ)评价了红霉素的生态风险。结果表明,风险区域主要集中在辽河、海河和珠江,部分区域点位存在一定的红霉素暴露生态风险。研究结论可为红霉素水质标准制定和流域水环境管理提供科学依据。     

中国典型河湖水体铅的水生生物安全基准与生态风险评价

采用物种敏感度排序法(SSR)对我国铅的淡水水生生物安全基准进行推导,并以太湖为例进行了流域水生生物安全基准推导。对于难以获得的本土生物毒性数据,开展了相应的毒性试验。获得了我国国家与太湖流域铅的水生生物安全基准值,基准最大浓度(CMC)分别为63.92、104.26μg·L-1,基准连续浓度(CCC)分别为1.21、4.06μg·L-1。同时,对我国主要河流以及太湖流域进行了铅的生态风险评价,联合概率曲线法显示影响5%水生生物种类的概率分别为66.22%和43.19%,熵值法则显示中国主要河流存在较大的铅暴露风险,因此,我国铅的潜在生态风险较大,主要河流与太湖流域存在铅污染问题。     

物种敏感度分布法（SSD）在农药水质基准推导中的应用

水质基准推导方法在水质基准制定中起着至关重要的作用,物种敏感度分布法是目前国际上常用的基准推导方法,但利用此方法推导水质基准时,可选用的模型很多,但并不是所有的模型都能很好地拟合农药毒性数据集。为了筛选得到拟合优度较好的模型,选取4种典型农药,对采用不同模型拟合物种敏感度分布曲线的结果进行比较研究。结果显示,sigmoid、Gaussian、Gompertz和exponential growth 4种模型对于农药数据集,无论是在曲线走势、HC5值的合理性还是拟合优度方面的拟合效果都优于其他几种模型。因此,在应用物种敏感度分布法推导农药水质基准时,可以首选上述4种模型进行拟合,然后再从中选出最优模型来确定基准值,从而保证基准值推导的科学性。研究结果可为农药水质基准制定时推导方法的选择提供科学参考。     

Modeling survival and mark loss in molting animals: recapture, dead recoveries, and exuvia recoveries

Capture-mark-recapture (CMR) analyses aim primarily at estimating relevant life history parameters, despite the fact that some individuals are not always recaptured, even if alive on the study site. Applying such approaches to species with a complex life cycle, such as insects, remains challenging because each change of stage tends to cause mark loss through molting. We developed a multistate model based on three exclusive events ("dead", "surviving and molting", and "surviving and staying in the same larval stage") to estimate probabilities of survival and mark loss. Estimates of biologically relevant parameters were derived from those of the probabilities of transition between these states. The model was applied to data from radio-tracking diodes glued on grasshoppers. The estimates of recapture probabilities decreased throughout the season for animals remaining alive, while the detection of dead animals and lost diodes was exhaustive. The survival probability was higher for larvae than for adults (0.98 vs. 0.96), and mark loss was stronger in larvae than in adults (0.09 vs. 0.06). We show that the survival rate of a species with a high rate of mark loss can be estimated using multistate models, provided that marks can be recovered after being lost. These models are flexible enough to test for several effects that potentially affect survival and mark loss probabilities.     

Implications of different population model structures for management of threatened plants

Population viability analysis (PVA) is a reliable tool for ranking management options for a range of species despite parameter uncertainty. No one has yet investigated whether this holds true for model uncertainty for species with complex life histories and for responses to multiple threats. We tested whether a range of model structures yielded similar rankings of management and threat scenarios for 2 plant species with complex postfire responses. We examined 2 contrasting species from different plant functional types: an obligate seeding shrub and a facultative resprouting shrub. We exposed each to altered fire regimes and an additional, species‐specific threat. Long‐term demographic data sets were used to construct an individual‐based model (IBM), a complex stage‐based model, and a simple matrix model that subsumes all life stages into 2 or 3 stages. Agreement across models was good under some scenarios and poor under others. Results from the simple and complex matrix models were more similar to each other than to the IBM. Results were robust across models when dominant threats are considered but were less so for smaller effects. Robustness also broke down as the scenarios deviated from baseline conditions, likely the result of a number of factors related to the complexity of the species’ life history and how it was represented in a model. Although PVA can be an invaluable tool for integrating data and understanding species’ responses to threats and management strategies, this is best achieved in the context of decision support for adaptive management alongside multiple lines of evidence and expert critique of model construction and output.     

化学品生态毒性测试鱼类模式生物的应用与展望

水生生物毒性测试广泛应用于评估化学品的水生态环境安全,而鱼类生态毒性数据为水生生态风险评估与风险管理提供基础。本文总结了现有的鱼类水生毒性测试标准及常用的物种。阐述了常用水生鱼类模式生物,如斑马鱼Danio rerio、青鳉鱼Oryzias latipes、黑头软口鲦Pimephales promelas等作为模式鱼类的特征及在生态毒性测试中的应用。环保部7号令推荐稀有鮈鲫Gobiocypris rarus作为中国本土生物在水生毒性测试中使用。目前公开发表的利用稀有鮈鲫的水生毒性研究多集中在急性毒性方面,对其他类型的研究如法规毒理相关的长期慢性毒性有待开展。     

Inferring extinction of mammals from sighting records, threats, and biological traits

For species with five or more sightings, quantitative techniques exist to test whether a species is extinct on the basis of distribution of sightings. However, 70% of purportedly extinct mammals are known from fewer than five sightings, and such models do not include some important indicators of the likelihood of extinction such as threats, biological traits, search effort, and demography. Previously, we developed a quantitative method that we based on species' traits in which we used Cox proportional hazards regression to calculate the probability of rediscovery of species regarded as extinct. Here, we used two versions of the Cox regression model to determine the probability of extinction in purportedly extinct mammals and compared the results of these two models with those of stationary Poisson, nonparametric, and Weibull sighting-distribution models. For mammals with five or more sightings, the stationary Poisson model categorized all but two critically endangered (flagged as possibly extinct) species in our data set as extinct, and results with this model were consistent with current categories of the International Union for the Conservation of Nature. The scores of probability of rediscovery for individual species in one version of our Cox regression model were correlated with scores assigned by the stationary Poisson model. Thus, we used this Cox regression model to determine the probability of extinction of mammals with sparse records. On the basis of the Cox regression model, the most likely mammals to be rediscovered were the Montane monkey-faced bat (Pteralopex pulchra), Armenian myotis (Myotis hajastanicus), Alcorn's pocket gopher (Pappogeomys alcorni), and Wimmer's shrew (Crocidura wimmeri). The Cox model categorized two species that have recently disappeared as extinct: the baiji (Lipotes vexillifer) and the Christmas Island pipistrelle (Pipistrellus murrayi). Our new method can be used to test whether species with few records or recent last-sighting dates are likely to be extinct.     

太湖流域3种氯酚类化合物水质基准的探讨

按照美国地面水水质基准制定的程序和规范,筛选了太湖流域广泛存在的水生生物物种并收集了相应的基础毒性数据,探讨了五氯酚(PCP)、2,4-二氯酚(2,4-DCP)和2,4,6-三氯酚(2,4,6-TCP)在我国太湖地区的水生态基准的定值.同时采用蒙特卡罗构建物种敏感度分布(SSD)曲线和生态毒理模型方法预测了3种氯酚类化合物对太湖水生生物的急性基准浓度(CMC)和慢性基准浓度(CCC).结果表明,基于EPA规范方法和急慢性毒性比率得到的PCP、2,4-DCP和2,4,6-TCP3种氯酚类化合物的CMC值分别为25、908和594μg·L-1,CCC值分别为12、176和162μg·L-1;基于SSD曲线得到的CMC值分别为25、818和648μg·L-1,CCC值分别为6、75和198μg·L-1;基于生态毒理模型得到的CCC值分别为4、15和67μg·L-1,显示出3种方法得到的氯酚类化合物的CMC或CCC在同一个数量级上,但在数值上由生态毒理模型得出的CCC要小于其它两种方法,并且除PCP的急慢性基准值与美国EPA推出的水生态基准值相近外,其它两种氯酚类化合物的急慢性基准值均低于美国EPA推出的急慢性基准值.研究结果希望能为我国水质基准的制定提供一些有用的线索.     

Incorporating low-resolution historic species location data decreases performance of distribution models

Developing robust species distribution models is important as model outputs are increasingly being incorporated into conservation policy and management decisions. A largely overlooked component of model assessment and refinement is whether to include historic species occurrence data in distribution models to increase the data sample size. Data of different temporal provenance often differ in spatial accuracy and precision. We test the effect of inclusion of historic coarse-resolution occurrence data on distribution model outputs for 187 species of birds in Australian tropical savannas. Models using only recent (after 1990), fine-resolution data had significantly higher model performance scores measured with area under the receiver operating characteristic curve (AUC) than models incorporating both fine- and coarse-resolution data. The drop in AUC score is positively correlated with the total area predicted to be suitable for the species (R² = 0.163-0.187, depending on the environmental predictors in the model), as coarser data generally leads to greater predicted areas. The remaining unexplained variation is likely to be due to the covariate errors resulting from resolution mismatch between species records and environmental predictors. We conclude that decisions regarding data use in species distribution models must be conscious of the variation in predictions that mixed-scale datasets might cause.     

Improving effectiveness of systematic conservation planning with density data

Systematic conservation planning aims to design networks of protected areas that meet conservation goals across large landscapes. The optimal design of these conservation networks is most frequently based on the modeled habitat suitability or probability of occurrence of species, despite evidence that model predictions may not be highly correlated with species density. We hypothesized that conservation networks designed using species density distributions more efficiently conserve populations of all species considered than networks designed using probability of occurrence models. To test this hypothesis, we used the Zonation conservation prioritization algorithm to evaluate conservation network designs based on probability of occurrence versus density models for 26 land bird species in the U.S. Pacific Northwest. We assessed the efficacy of each conservation network based on predicted species densities and predicted species diversity. High‐density model Zonation rankings protected more individuals per species when networks protected the highest priority 10‐40% of the landscape. Compared with density‐based models, the occurrence‐based models protected more individuals in the lowest 50% priority areas of the landscape. The 2 approaches conserved species diversity in similar ways: predicted diversity was higher in higher priority locations in both conservation networks. We conclude that both density and probability of occurrence models can be useful for setting conservation priorities but that density‐based models are best suited for identifying the highest priority areas. Developing methods to aggregate species count data from unrelated monitoring efforts and making these data widely available through ecoinformatics portals such as the Avian Knowledge Network will enable species count data to be more widely incorporated into systematic conservation planning efforts.     

Calculating Ne and Ne/N in age-structured populations: a hybrid Felsenstein-Hill approach

The concept of effective population size (Ne) was developed under a discrete-generation model, but most species have overlapping generations. In the early 1970s, J. Felsenstein and W. G. Hill independently developed methods for calculating Ne in age-structured populations; the two approaches produce the same answer under certain conditions and have contrasting advantages and disadvantages. Here, we describe a hybrid approach that combines useful features of both. Like Felsenstein's model, the new method is based on age-specific survival and fertility rates and therefore can be directly applied to any species for which life table data are available. Like Hill, we relax the restrictive assumption in Felsenstein's model regarding random variance in reproductive success, which allows more general application. The basic principle underlying the new method is that age structure stratifies a population into winners and losers in the game of life: individuals that live longer have more opportunities to reproduce and therefore have a higher mean lifetime reproductive success. This creates different classes of individuals within the population, and grouping individuals by age at death provides a simple means of calculating lifetime variance in reproductive success of a newborn cohort. The new method has the following features: (1) it can accommodate unequal sex ratio and sex-specific vital rates and overdispersed variance in reproductive success; (2) it can calculate effective size in species that change sex during their lifetime; (3) it can calculate Ne and the ratio Ne/N based on various ways of defining N; (4) it allows one to explore the relationship between Ne and the effective number of breeders per year (Nb), which is a quantity that genetic estimators of contemporary Ne commonly provide information about; and (5) it is implemented in freely available software (AgeNe).