Benthic nematode assemblage composition and diversity during a natural recovery process of Zostera noltii seagrass beds,

In 2008, the stable seagrass beds of the Mira estuary (SW Portugal) disappeared completely; however, during 2009, they have begun to present early symptoms of natural recovery, characterised by a strongly heterogeneous distribution. This study was designed to investigate the spatial and temporal variability patterns of species composition, densities and trophic composition of the benthic nematode assemblages in this early recovery process, at two sampling sites with three stations each and at five sampling occasions. Because of the erratic and highly patchy seagrass recovery and the high environmental similarity of the two sampling sites, we expected within-site variability in nematode assemblages to exceed between-site variability. However, contrary to that expectation, whilst nematode genus composition was broadly similar between sites, nematode densities differed significantly between sites, and this between-site variability exceeded within-site variability. This may be linked to differences in the Zostera recovery patterns between both sites. In addition, no clear temporal patterns of nematode density, trophic composition and diversity were evident.

Age and Gender Identification using Stacking for Classification⋆ Notebook for PAN at CLEF 2016

This paper presents our approach of identifying the profile of an unknown user based on the activities of known users. The aim of author profiling task of PAN@CLEF 2016 is cross-genre identification of the gender and age of an unknown user. This means training the system using the behavior of different users from one social media platform and identifying the profile of other user on some different platform. Instead of using single classifier to build the system we used a combination of different classifiers, also known as stacking. This approach allowed us explore the strength of all the classifiers and minimize the bias or error enforced by a single classifier.