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Pollution Bioindicators: Statistical Analysis of a Case Study

机译:污染生物指标:个案研究的统计分析

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In this paper a three-step procedure is proposed to deal with ecological data, usually very complex in their treatment. The three steps - exploratory, confirmatory, and modelling phases - reflect the different methodological approaches necessary in each phase of the study. To illustrate the methodology, a case study is proposed, concerning the suitability of plants as pollution bioindicators. Samples of differently aged Pinus pinea L. needles were collected throughout 1 year in three different locations, whose human disturbance was known to be different. In the samples some morphological and functional parameters were measured, whose relation with the stress was already known. The exploratory analysis suggested pollution with human origin, the needle's age, and the environmental conditions as the main factors of influence of damage. The confirmatory analysis confirmed both site and age as main factors and occasionally the sampling date. On this basis, some models were estimated separately for each site: models that best described the damage as function of age resulted nonlinear and some of them with seasonal fluctuations. As a result, whereas the models described well enough the pollution temporal variation, the difference of pollution in the sites was best described by the different values of the models parameters in the different sites. In short, different pollution conditions are described better by the damage trend than by the individual measures. The three-step procedure resulted of high utility in outlining the most interesting relations to investigate through the modelling, the opportunity to model the indicators variation along time separately for each site, and to introduce the seasonal variation in some models.
机译:本文提出了一个三步程序来处理生态数据,通常在处理过程中非常复杂。探索,验证和建模阶段这三个步骤反映了研究每个阶段所需的不同方法论方法。为了说明该方法,提出了一个案例研究,涉及植物作为污染生物指标的适用性。整个1年中,我们在三个不同的地点收集了不同年龄的松树松针的样品,这些地方的人为干扰有所不同。在样品中测量了一些形态和功能参数,它们与应力的关系是已知的。探索性分析表明,人为污染,针头的年龄和环境条件是造成损害的主要因素。验证性分析确认了场地和年龄是主要因素,偶尔也确定了采样日期。在此基础上,针对每个站点分别评估了一些模型:最能描述损害与年龄相关的模型是非线性的,而某些模型则具有季节性波动。结果,尽管模型描述的污染时间变化足够好,但不同地点模型参数的不同值最好地描述了地点的污染差异。简而言之,对于不同的污染条件,用损害趋势比用单独的措施更好地描述。该三步程序具有很高的实用性,它可以概述最有趣的关系以通过建模进行调查,可以为每个站点分别建模随时间变化的指标,并在某些模型中引入季节变化。

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