鲁中南岩溶塌陷区岩溶水污染途径研究

在鲁中南岩溶发育区,由于过量开采岩溶地下水,岩溶塌陷频繁发生,岩溶地下水也受到不同程度的污染。在岩溶塌陷区,岩溶地下水污染与岩溶塌陷有着密切联系。岩溶塌陷的条件、规模、频度、塌陷的时空阶段性等都直接影响岩溶地下水的污染程度。根据岩溶水的补给途径,岩溶水污染途径主要有四种:面状垂直渗透污染、带状侧向渗漏污染、点状塌陷坑灌入污染和超采岩溶水激发越流污染,不同的污染途径其污染源也不相同。要防止岩溶水污染,必须从根本上解决岩溶塌陷问题,切断污染途径,加强岩溶塌陷的防治和监测,从而保证岩溶水资源可持续发展。     

Evolution,variability and sustainable development

SUMMARY

Sustainable development is a global challenge to science and society. In politics and economics the concepts for establishing a sustainable society are numerous, nonetheless necessary interdisciplinary approaches are still marginalised. Trying to foster a deeper communication between biology and social science, an evolutionary perspective on sustainable development is offered. Subsequently, the role of variability and diversity in evolution is highlighted. Hereby, special attention is devoted, among other things, to the links between variability and stability in the long term. Next, selection and variability are emphasised in the cultural context. This is followed by general implications for sustainability. In contrast to strategies aiming at short-term optimisation and economic efficiency, we argue that the conditions and circumstances maintaining variability and momentary sub-optimal alternatives are highly relevant for a socio-economic system that is heading for sustainable development.     

Implementing second-best environmental policy under adverse selection

A key obstacle to practical application of mechanism design theory to regulation is the difficulty of obtaining consistent beliefs regarding information that theoretical models assume to be commonly held. This article presents a solution to this problem by developing an easily implemented empirical methodology with which the government can use available data to develop beliefs regarding the technology and distribution of types in a regulated sector characterized by hidden information. Results are used to calibrate a second-best land conservation mechanism and evaluate its cost relative to simpler alternatives.     

Sexual selection in a socially monogamous bird: male color predicts paternity success in the mountain bluebird, <Emphasis Type="Italic">Sialia currucoides</Emphasis>

Ornamental traits are thought to evolve because they give individuals an advantage in securing multiple mates. Thus, the presence of ornamentation among males in many monogamous bird species presents something of a conundrum. Under certain conditions, extra-pair paternity can increase the variance in reproductive success among males, thus increasing the potential for sexual selection to act. We addressed this possibility in the mountain bluebird (Sialia currucoides), a socially monogamous songbird in which males possess brilliant ultraviolet (UV)-blue plumage. Specifically, we asked whether a male’s success at siring offspring within his own nest and within the nests of other males was related to his coloration. In pairwise comparisons, males that sired extra-pair offspring were not more colorful than the males that they cuckolded. However, males that sired at least one extra-pair offspring were, on average, brighter and more UV-blue than males that did not sire extra-pair offspring. Brighter, more UV-blue males sired more offspring both with their own mate and tended to sire more offspring with extra-pair mates and thus sired more offspring overall. Our results support the hypothesis that the brilliant UV-blue ornamental plumage of male mountain bluebirds evolved at least in part because it provides males with an advantage in fertilizing the eggs of multiple females.     

The effect of perceived female parasite load on post-copulatory male choice in a sex-role-reversed pipefish

The last several decades of research in behavioral ecology have resulted in a deeper appreciation of post-mating processes and sexual conflict in sexual selection. One of the most controversial aspects of sexual selection is cryptic mate choice. Here, we take advantage of male pregnancy in a sex-role-reversed pipefish (Syngnathus typhle) to quantify cryptic choice based on perceived parasite load and other sources of variance in female fitness. Studies have shown that S. typhle males preferentially mate with females with lower parasite loads and that a male’s perception of female parasite load can be altered by tattooing females. We manipulated the apparent parasite load of females in controlled mating experiments to test the hypothesis that post-copulatory sexual selection is dependent on a male’s perception of female parasite load in pipefish. Our results provided no evidence for cryptic male choice based on perceived female parasite load. However, we found evidence that eggs from larger females were more likely to result in viable offspring than eggs from smaller females and that the first female to mate with a male transferred more eggs per copulation on average. Overall, our results show that potential for post-copulatory sexual selection does exist in pipefish, but the male’s perception of female parasite load does not play a major role in this process.     

不同地区土壤古菌群落对重金属污染的响应

为探讨农田土壤古菌群落结构与构建机制对不同类型重金属污染的响应特征及影响因素,采集高地质背景区、涉重金属企业和工矿区周边农田土壤样品,通过高通量测序,结合土壤理化性质,对土壤古菌群落组成及构建机制进行研究.结果表明,本研究区域内农田土壤重金属空间异质性高,镉污染较广泛,除工矿区部分土壤样本存在强生态风险,其他样本存在轻微的潜在生态风险.不同地区古菌群落结构差异较大,泉古菌门（Crenarchaeota）为优势菌门,占比62.7%~98.3%,其次为Halobacterota （1.1%~23.2%）.环境因子中,土壤有机质含量、pH、砷和铅含量与古菌群落显著相关（P<0.05）,是古菌群落结构差异的主要驱动因子.零模型分析表明本研究古菌群落在系统发育上聚集,确定性过程驱动古菌群落构建,有机质和pH等环境因子的异质选择作用主导古菌群落形成.因此,环境过滤的确定性作用最终驱动本研究古菌群落构建,环境异质性导致了古菌群落多样性和空间异质性,从而增强古菌抵御环境胁迫的能力,利于农田生态系统功能的稳定性和可持续性.     

人工湿地植物量及其对净化效果影响的研究

人工湿地污水处理系统中,植物对污水净化效果起着非常重要的作用,而植物量是植物生长的关键参数之一。为了明确植物量对污水处理效果的影响,在2002--2008年期间,详细测定了芦苇（Ph．australisTrin）、再力花（Thaliadealbata）、荻（M．sacchariflorus）和美人蕉（Cannaindica）4种典型湿地植物不同年度的生物量、不同生长阶段的生物量、生物量年产率,以及同期湿地COD、BOD5、TN和TP等的去除率。结果表明：湿地植物在栽植成活、稳定生长以后,至少要再经过1个以上的生长周期才能完全适应湿地环境,达到生物量的最大值,其中芦苇根系和茎叶生物量显著高于其他植物;同种植物的植物量与COD、BOD5、TN去除率呈显著正相关,与TP相关性不强;植物量随生长周期的变化对湿地净化能力的影响显著,确定合理收割期有利于湿地的稳定运行;不同种类植物生物量年产率与各种污染物的去除率均显著相关,芦苇、再力花和美人蕉均具有较高的生物量年产率,污染物去除能力较好。在试验范围内,芦苇湿地的运行稳定性最好,再力花湿地具有最强的脱氮能力,美人蕉湿地能快速形成规模、实现稳定运行,这些为构建不同特点和不同需要的湿地提供了重要参考。     

平板膜-生物反应器中膜的优选

将膜特性与膜-生物反应器(MBR)运行状况相结合,进行3种膜的优选. 对3种膜进行膜表面形态、孔径、孔隙率及水通量、临界通量的测定,同时将其置于MBR中进行短期高通量连续恒流运行及长期低通量间歇恒流运行,考察2种运行模式下的跨膜压差(TMP)平均增长率(Δp). 结果表明:具有平整表面、最小孔径、高孔隙率、高水通量以及高临界通量的A膜在MBR长期运行中表现出最低的膜污染速率,因此确定A膜为3种膜中的最优膜;在优选具有工程适应性的膜时,应采用长期间歇恒流运行的方法.      

Using a model selection criterion to identify appropriate complexity in aquatic biogeochemical models

Aquatic biogeochemical models are widely used as tools for understanding aquatic ecosystems and predicting their response to various stimuli (e.g., nutrient loading, toxic substances, climate change). Due to the complexity of these systems, such models are often elaborate and include a large number of estimated parameters. However, correspondingly large data sets are rarely available for calibration purposes, leading to models that may be overfit and possess reduced predictive capabilities. We apply, for the first time, information-theoretic model-selection techniques to a set of spatially explicit (1D) algal dynamics models of varying parameter dimension. We demonstrate that increases in complexity tend to produce a better model fit to calibration data, but beyond a certain degree of complexity the benefits of adding parameters are diminished (the risk of overfitting becomes greater). The particular approach taken here is computationally expensive, but several suggestions are made as to how multimodel methods may practically be extended to more sophisticated models.     

An evaluation of three statistical methods used to model resource selection

The performance of statistical methods for modeling resource selection by animals is difficult to evaluate with field data because true selection patterns are unknown. Simulated data based on a known probability distribution, though, can be used to evaluate statistical methods. Models should estimate true selection patterns if they are to be useful in analyzing and interpreting field data. We used simulation techniques to evaluate the effectiveness of three statistical methods used in modeling resource selection. We generated 25 use locations per animal and included 10, 20, 40, or 80 animals in samples of use locations. To simulate species of different mobility, we generated use locations at four levels according to a known probability distribution across DeSoto National Wildlife Refuge (DNWR) in eastern Nebraska and western Iowa, USA. We either generated 5 random locations per use location or 10,000 random locations (total) within 4 predetermined areas around use locations to determine how the definition of availability and the number of random locations affected results. We analyzed simulated data using discrete choice, logistic-regression, and a maximum entropy method (Maxent). We used a simple linear regression of estimated and known probability distributions and area under receiver operating characteristic curves (AUC) to evaluate the performance of each method. Each statistical method was affected differently by number of animals and random locations used in analyses, level at which selection of resources occurred, and area considered available. Discrete-choice modeling resulted in precise and accurate estimates of the true probability distribution when the area in which use locations were generated was ≥ the area defined to be available. Logistic-regression models were unbiased and precise when the area in which use locations were generated and the area defined to be available were the same size; the fit of these models improved with increased numbers of random locations. Maxent resulted in unbiased and precise estimates of the known probability distribution when the area in which use locations were generated was small (home-range level) and the area defined to be available was large (study area). Based on AUC analyses, all models estimated the selection distribution better than random chance. Results from AUC analyses, however, often contradicted results of the linear regression method used to evaluate model performance. Discrete-choice modeling was best able to estimate the known selection distribution in our study area regardless of sample size or number of random locations used in the analyses, but we recommend further studies using simulated data over different landscapes and different resource metrics to confirm our results. Our study offers an approach and guidance for others interested in assessing the utility of techniques for modeling resource selection in their study area.