Schulz Marcus, van Loon Willem, Fleet David M, Baggelaar Paul, van der Meulen Eit
AquaEcology GmbH & Co. KG, Marie-Curie-Str. 1, 26129 Oldenburg, Germany.
Rijkswaterstaat, Ministry of Infrastructure and Environment, The Netherlands.
Mar Pollut Bull. 2017 Sep 15;122(1-2):166-175. doi: 10.1016/j.marpolbul.2017.06.045. Epub 2017 Jun 21.
The aim of this study is to develop standard statistical methods and software for the analysis of beach litter data. The optimal ensemble of statistical methods comprises the Mann-Kendall trend test, the Theil-Sen slope estimation, the Wilcoxon step trend test and basic descriptive statistics. The application of Litter Analyst, a tailor-made software for analysing the results of beach litter surveys, to OSPAR beach litter data from seven beaches bordering on the south-eastern North Sea, revealed 23 significant trends in the abundances of beach litter types for the period 2009-2014. Litter Analyst revealed a large variation in the abundance of litter types between beaches. To reduce the effects of spatial variation, trend analysis of beach litter data can most effectively be performed at the beach or national level. Spatial aggregation of beach litter data within a region is possible, but resulted in a considerable reduction in the number of significant trends.
本研究的目的是开发用于分析海滩垃圾数据的标准统计方法和软件。统计方法的最佳组合包括曼-肯德尔趋势检验、泰尔-森斜率估计、威尔科克森步长趋势检验和基本描述性统计。将专门用于分析海滩垃圾调查结果的软件Litter Analyst应用于北海东南部七个海滩的奥斯巴公约海滩垃圾数据，结果显示在2009 - 2014年期间，海滩垃圾类型的丰度存在23个显著趋势。Litter Analyst显示不同海滩之间垃圾类型的丰度差异很大。为了减少空间变异的影响，海滩垃圾数据的趋势分析最有效地在海滩或国家层面进行。对一个区域内的海滩垃圾数据进行空间汇总也是可行的，但这导致显著趋势的数量大幅减少。
