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Biomonitoring river diatoms: Implications of taxonomic resolution

机译:河流硅藻生物监测:分类学意义

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摘要

Benthic diatoms are routinely used to assess river pollution. Most of the tools based on these organisms exploit the differences of pollution sensitivity between species; as such, species level identification is required. Accurate determination of diatom species requires rigorous training due to the extreme diversity of the group. The level of taxonomic resolution for biomonitoring is still debated. We tested the influence of taxonomic resolution on diatom bioassessment in an ecoregional framework. We used a database of 1967 diatom samples from biomonitoring programs in two French river basins, that reported three kinds of data for each site: (a) taxa abundance, expressed with 6 separate level of taxonomic resolution: species, genus, family, order, class or subdivision level; (b) physical and chemical characterization; (c) ecoregion and river-size class memberships. Mantel tests showed that the influence of taxonomic resolution on assemblage composition description was weak from species to order level. Mantel tests between chemical parameters and diatom assemblages showed that there was an increase in correlation from subdivision to genera resolution. But species and genus resolutions showed equivalent correlations with chemical parameters. Predictive models using diatom data to reconstruct nutrients, organic matter and major-ions content showed an increasing performance from sub-division to species resolution. Nevertheless their performances did not follow the exponential increase of taxa number from sub-division to species: models performances improved only by 12-23% from genus to species depending on the parameter reconstructed whereas number of taxa was multiplied by 10. Finally, we observed that the more precise the taxonomic resolution, the better the correspondence with ecoregion classification. This can be partly explained by diatom endemism and cosmopolitanism which is mostly observed to species level, rarely to genus level and never above.For a quick and robust assessment of river pollution coarse identification is sufficient. Hypotheses to explain such results are that: (1) many species are too rare to describe their ecological requirements with certainty; (2) more environmental descriptors are necessary to explain the presence of some species; (3) the dataset is compromised by identification errors, particularly at the species level. On the other hand, a precise ecoregional bioassessment requires a fine taxonomic resolution; this must be stressed for the European Water Framework Directive which requires an assessment in an ecoregion classification.
机译:底栖硅藻通常用于评估河流污染。基于这些生物的大多数工具都利用物种之间的污染敏感性差异。因此,需要对物种级别进行识别。由于硅藻种类极多,因此准确确定硅藻种类需要严格的培训。生物监测的生物分类分辨率水平仍在争论中。我们在生态区域框架内测试了分类学分辨率对硅藻生物评估的影响。我们使用了来自法国两个流域生物监测计划的1967年硅藻样品的数据库,该数据库报告了每个站点的三种数据:(a)分类群丰富度,用6种不同的分类学分辨率表示:物种,属,科,序,类或细分级别; (b)物理和化学特性; (c)生态区和河流级成员。壁炉架测试表明,从物种到阶次,分类学分辨率对组合物组成描述的影响都很弱。化学参数与硅藻组合物之间的Mantel测试表明,从细分到属分辨率的相关性增加。但是物种和属的分辨率显示出与化学参数的等价相关性。使用硅藻数据重建养分,有机质和主要离子含量的预测模型显示出从细分到物种分解的性能不断提高。然而,它们的性能并未遵循从细分到物种的分类单元数量的指数增长:模型性能从属到物种仅提高了12-23%,具体取决于重构的参数,而分类单元的数量乘以10。最后,我们观察到分类学分辨率越精确,与生态区分类的对应关系就越好。这可以部分由硅藻特有和世界主义来解释,这主要是在物种水平上观察到的,很少在属水平上观察到,并且从不高于此水平。对于快速而稳健的河流污染评估,粗略识别就足够了。解释这种结果的假设是:(1)许多物种太稀少,无法确切地描述其生态需求; (2)需要更多的环境描述符来解释某些物种的存在; (3)数据集由于识别错误而受损,尤其是在物种级别。另一方面,精确的生态区域生物评估需要精细的分类学分辨率;必须针对欧洲水框架指令强调这一点,该指令要求对生态区域分类进行评估。

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