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1.
Successful implementation of the Water Framework Directive and achieving its objective of good ecological status of all water bodies depend on the power of the set of monitoring indicators to capture the change in the ecological status of aquatic systems. In this context, testing the robustness and sensitivity of ecological indicators currently used for assessing the status of lotic water bodies is instrumental for the adaptation and further development of assessment methods. This is also a prerequisite for an effective, context-based monitoring system and for improving the quality of the decision making for water bodies. This is particularly challenging in regions where the sets of indicators are under development, the data series are relatively short and data which addresses the individual error sources are lacking. Here we show that hierarchical clusters and ordination analysis provide appropriate tools with which the validity of the ecological status of water bodies set up based on biological multimetric monitoring indices in a small water basin could be tested. We hypothesize that robust and informative monitoring methods classify all water bodies belonging to a single ordination grouping in the same quality class (high, good, moderate, poor or bad). In our case study multimetric biological indicators failed to discriminate between the good and moderate ecological status. Community structure as well as water conductivity and nitrate load were primarily responsible for the observed difference between ordination groupings. Inconsistencies shown in our case study are likely to be induced by insufficient refinement of monitoring schemes and by the constraints existing in the data series and available metadata. We show that multiplication of indicators leads to discrepant interpretation and problematic application. Proposed ordination analysis proves to be a simple and useful tool to detect such discrepancies and support further progress in indicator development. Integrated and longer data and metadata series are needed to refine context-based monitoring methods.  相似文献   
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  • Studies on plant electrophysiology are mostly focused on specific traits of single cells. Inspired by the complexity of the signalling network in plants, and by analogy with neurons in human brains, we sought evidence of high complexity in the electrical dynamics of plant signalling and a likely relationship with environmental cues.
  • An EEG‐like standard protocol was adopted for high‐resolution measurements of the electrical signal in Glycine max seedlings. The signals were continuously recorded in the same plants before and after osmotic stimuli with a ?2 MPa mannitol solution. Non‐linear time series analyses methods were used as follows: auto‐correlation and cross‐correlation function, power spectra density function, and complexity of the time series estimated as Approximate Entropy (ApEn).
  • Using Approximate Entropy analysis we found that the level of temporal complexity of the electrical signals was affected by the environmental conditions, decreasing when the plant was subjected to a low osmotic potential. Electrical spikes observed only after stimuli followed a power law distribution, which is indicative of scale invariance.
  • Our results suggest that changes in complexity of the electrical signals could be associated with water stress conditions in plants. We hypothesised that the power law distribution of the spikes could be explained by a self‐organised critical state (SOC) after osmotic stress.
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The usefulness of benthic multi-metric indices when assessing seafloor integrity across broad environmental gradients should be deliberated, as their lack of transparency might hide important sources of variation and fail to identify environmental change. This study compares the performance of two multi-metric indices; the Benthic Quality Index (BQI) and the Brackish water Benthic Index (BBI) between three sub-basins in the Baltic Sea. Both indices reflect the salinity-driven gradient in macroinvertebrate diversity and composition as well as changes in bottom water oxygen concentrations. The relative contribution of predictor variables for explaining index variation does, however, differ between sub-basins, resulting in the indices representing different aspects of the benthic community along the environmental gradient. This context-dependency is caused by inherent differences in benthic community characteristics between the sub-basins of the Baltic Sea, and how the communities are portrayed by the indices. An increased transparency of the importance of the different predictors for directing index values is needed for coherent classifications over broad environmental gradients, such as those occurring in large estuarine water bodies. Use of a weight of evidence table to combine multiple indicators would preserve transparency and be more likely to provide a robust assessment method that would detect seafloor degradation at an early stage.  相似文献   
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土壤病毒生态学研究方法   总被引:5,自引:1,他引:4  
韩丽丽  于丹婷  贺纪正 《生态学报》2017,37(6):1749-1756
病毒是地球上最丰富的生物实体,每克土壤中可包含数以亿计的病毒,它不仅影响土壤中其它微生物的群落组成、土壤元素的生物地球化学循环,还会影响土壤微生物的物种进化,甚至影响植物、动物和人体健康。目前人们对土壤中病毒的种类及丰度、分布特征以及功能引起的生态环境效应还知之甚少。在概述病毒生态学研究方法的基础上,对土壤病毒的提取、纯化、定量及分子生态学方法等基本流程进行了比较分析,以期建立一套快速简便、高效稳定的适用于土壤病毒研究的方法,并用于研究土壤病毒的多样性及分布特征,探讨病毒在环境中的生存和传播机制,为土壤病毒的防控及开发利用提供支撑。  相似文献   
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