Benthic meiofauna community composition at polluted and non-polluted sites in New Zealand intertidal environments   总被引：1，自引：0，他引：1  

Hack LA  Tremblay LA  Wratten SD  Lister A  Keesing V 《Marine pollution bulletin》2007,54(11):1801-1812

Meiofauna composition was investigated for six field sites, including polluted and non-polluted sites, within two regions (Auckland and Bay of Plenty) during winter (July-August 2004) in the North Island of New Zealand. Physico-chemical parameters were measured during the sampling period and meiofauna distribution and abundance were compared with these measured parameters. Analysis of meiofauna abundance indicated that foraminiferans, nematodes and ostracods were the taxa that contributed to the variability between field sites within the Auckland region. However, no clear taxa dominance was seen in the Bay of Plenty region. Comparison of meiofauna abundance and physico-chemical parameters was done using multivariate analysis (PRIMER). However, no clear relationships between the parameters were observed in any field site in either region. The Shannon-Weiner index of diversity did not show any clear differentiation between polluted and non-polluted field sites. Therefore, from the present study, the taxa or physico-chemical parameters used could not effectively characterise pollution at the investigated field sites.  相似文献   

Separating wheat from chaff: Diatom taxon selection usingan artificial neural network pruning algorithm     

Julien M.J. Racca  Matthew Wild  H.J.B. Birks  Yves T. Prairie 《Journal of Paleolimnology》2003,29(1):123-133

This study addresses the question of what diatom taxa to includein a modern calibration set based on their relative contribution in apalaeolimnological calibration model. Using a pruning algorithm for ArtificialNeural Networks (ANNs) which determines the functionality of individual taxa interms of model performance, we pruned the Surface Water Acidification Project(SWAP) pH-diatom data-set until the predictive performance of thepruned set (as assessed by a jackknifing procedure) was statistically differentfrom the initial full-set. Our results, based on the validation at each5% data-set reduction, show that (i) 85% of the taxa canbe removed without any effect on the pH model calibration performance, and (ii)that the complexity and the dimensionality reduction of the model by theremoval of these non-essential or redundant taxa greatly improve therobustness of the calibration. A comparison between the commonly usedmarginal criteria for inclusion (species tolerance andHill's N2) and our functionality criterion shows that the importance ofeach taxon in an ANN palaeolimnological model calibration does not appear todepend on these marginal characteristics.  相似文献