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将特征纳入水生生物监测,以增强因果诊断和预测。

Incorporating traits in aquatic biomonitoring to enhance causal diagnosis and prediction.

机构信息

Environment Canada, NWRI, University of New Brunswick, 10 Bailey Drive, Fredericton, NB E3B5A3, Canada.

出版信息

Integr Environ Assess Manag. 2011 Apr;7(2):187-97. doi: 10.1002/ieam.128. Epub 2010 Aug 3.

Abstract

The linkage of trait responses to stressor gradients has potential to expand biomonitoring approaches beyond traditional taxonomically based assessments that identify ecological effect to provide a causal diagnosis. Traits-based information may have several advantages over taxonomically based methods. These include providing mechanistic linkages of biotic responses to environmental conditions, consistent descriptors or metrics across broad spatial scales, more seasonal stability compared with taxonomic measures, and seamless integration of traits-based analysis into assessment programs. A traits-based biomonitoring approach does not require a new biomonitoring framework, because contemporary biomonitoring programs gather the basic site-by-species composition matrices required to link community data to the traits database. Impediments to the adoption of traits-based biomonitoring relate to the availability, consistency, and applicability of existing trait data. For example, traits generalizations among taxa across biogeographical regions are rare, and no consensus exists relative to the required taxonomic resolution and methodology for traits assessment. Similarly, we must determine if traits form suites that are related to particular stressor effects, and whether significant variation of traits occurs among allopatric populations. Finally, to realize the potential of traits-based approaches in biomonitoring, a concerted effort to standardize terminology is required, along with the establishment of protocols to ease the sharing and merging of broad, geographical trait information.

摘要

特质反应与胁迫梯度的联系有可能扩展生物监测方法,超越传统的基于分类的评估,这种评估方法确定生态效应,提供因果诊断。基于特质的信息可能比基于分类的方法具有几个优势。这些优势包括为生物对环境条件的反应提供机制联系、在广泛的空间尺度上具有一致的描述符或指标、与分类学措施相比具有更高的季节性稳定性,以及将基于特质的分析无缝集成到评估计划中。基于特质的生物监测方法不需要新的生物监测框架,因为当代生物监测计划收集了将群落数据与特质数据库联系起来所需的基本站点-物种组成矩阵。采用基于特质的生物监测的障碍与现有特质数据的可用性、一致性和适用性有关。例如,生物地理区域内各分类群之间的特质概括很少见,而且在特质评估所需的分类分辨率和方法方面也没有共识。同样,我们必须确定特质是否形成与特定胁迫效应相关的特征组合,以及特质在异域种群之间是否存在显著差异。最后,为了实现基于特质的方法在生物监测中的潜力,需要做出协调一致的努力来标准化术语,并建立协议,以方便广泛的地理特质信息的共享和合并。

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