首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Pollution Bioindicators: Statistical Analysis of a Case Study
Authors:Sergio Camiz  Antonella Altieri  Fausto Manes
Institution:1. Dipartimento di Matematica Guido Castelnuovo, Sapienza Università di Roma, Piazzale Aldo Moro, 2, I 00185, Rome, Italy
2. Laboratorio di Indagini Biologiche, Istituto Centrale del Restauro Ministero Beni e Attività Culturali, Rome, Italy
3. Dipartimento di Biologia Vegetale, Sapienza Università di Roma, Piazzale Aldo Moro, 2, I 00185, Rome, Italy
Abstract: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 non-linear 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.
Keywords:
本文献已被 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号